711 Artificial Intelligence (AI) Jobs in India

TECHJAYS

THE AI REIMAGINATION COMPANY

Position DevOps Lead

Experience 10+ Years

Location Coimbatore / Hybrid

Joining Immediate / ASAP

Primary SkillsDevOps, AWS or Azure, CI/CD, Kubernetes, Docker, Terraform, Linux, Git, Cloud Infrastructure, Infrastructure Automation, Monitoring & Observability

Preferred SkillsAI/ML Infrastructure Exposure, GenAI Applications, GitOps, Argo CD, Prometheus, Grafana, Python, Bash, PowerShell, Cloud Security, FinOps

About Techjays

At Techjays, we're helping businesses reimagine how they build, operate, and scale with AI at the core. We focus on developing secure, scalable, production-grade AI systems that solve complex business challenges and deliver measurable business outcomes.

Our team brings together experienced engineers and technology leaders from organizations such as Google, NetApp, ADP, Cognizant Consulting, and Capgemini. We work with global clients to build advanced AI-powered applications, enterprise platforms, and intelligent automation solutions.

We're looking for a DevOps Lead who can take ownership of cloud infrastructure, deployment automation, CI/CD pipelines, platform reliability, and engineering operations.

The ideal candidate will have deep hands-on expertise in either AWS or Azure, along with strong experience in Kubernetes, containerization, Infrastructure as Code, and production cloud environments.

You will lead the design and implementation of reliable infrastructure platforms, establish DevOps best practices, and work closely with software engineering and AI teams to support the deployment and operation of modern applications.

This role requires a strong hands-on cloud and DevOps specialist who can architect, implement, troubleshoot, and optimize production infrastructure. Prior exposure to AI/ML or AI-enabled applications is required, but specialized MLOps expertise is not mandatory.

Key Responsibilities

1. Cloud Infrastructure & Architecture

• Lead the design, implementation, and management of scalable, secure, and highly available cloud infrastructure.
• Own cloud infrastructure architecture and operations across AWS or Azure.
• Design and manage cloud environments covering compute, networking, storage, databases, and container platforms.
• Establish infrastructure standards, architecture patterns, and operational best practices.
• Manage cloud resource provisioning, configuration, scaling, and environment management.
• Ensure infrastructure meets requirements for availability, performance, security, and reliability.
• Drive infrastructure improvements through automation and continuous optimization.

2. DevOps & CI/CD Engineering

• Design, implement, and maintain CI/CD pipelines for application development and deployment.
• Manage multi-stage deployment workflows across development, testing, staging, and production environments.
• Implement automated build, testing, deployment, and release processes.
• Establish reusable pipeline templates, deployment standards, and approval workflows.
• Manage deployment strategies, including rolling, blue/green, and canary deployments.
• Implement rollback mechanisms and ensure reliable production releases.
• Integrate CI/CD workflows with source control, artifact repositories, and container registries.
• Continuously improve deployment efficiency, release reliability, and engineering productivity.

3. Containerization & Kubernetes Management

• Architect and manage containerized application environments using Docker and Kubernetes.
• Manage production Kubernetes clusters using Amazon EKS or Azure AKS.
• Implement Kubernetes configurations covering deployments, services, networking, secrets, storage, and resource management.
• Work with Helm charts for application packaging and deployment.
• Optimize container resource utilization, application scaling, and cluster performance.
• Troubleshoot complex container and Kubernetes-related production issues.
• Establish best practices for container security and workload reliability.

4. Infrastructure as Code & Automation

• Implement Infrastructure as Code using Terraform and cloud-native provisioning tools.
• Automate infrastructure provisioning, configuration management, and environment setup.
• Develop reusable infrastructure modules and deployment automation workflows.
• Use Python, Bash, or PowerShell to automate operational tasks and improve efficiency.
• Reduce manual intervention through standardization and automation.
• Maintain infrastructure documentation, configuration standards, and version-controlled deployment workflows.

5. Monitoring, Reliability & Production Operations

• Establish centralized monitoring, logging, alerting, and observability across cloud environments.
• Implement monitoring solutions using CloudWatch, Azure Monitor, Prometheus, Grafana, or equivalent platforms.
• Monitor application availability, infrastructure health, resource utilization, and system performance.
• Lead troubleshooting and resolution of complex production incidents.
• Conduct root cause analysis and implement permanent corrective actions.
• Establish operational practices for backup, disaster recovery, availability, and business continuity.
• Improve system reliability through proactive monitoring and performance optimization.

6. Cloud Security & Governance

• Implement cloud security best practices across infrastructure and application environments.
• Manage IAM, RBAC, access controls, service identities, and secrets management.
• Secure cloud networking, virtual networks, firewalls, and infrastructure access.
• Implement container security and infrastructure hardening practices.
• Ensure cloud environments follow organizational security and compliance requirements.
• Identify infrastructure vulnerabilities and coordinate remediation activities.
• Establish secure deployment and configuration management practices.

7. AI Infrastructure & Engineering Collaboration

• Work closely with AI/ML and software engineering teams to provide infrastructure for AI-powered applications.
• Support the deployment and operation of LLM-based applications, AI services, and AI-enabled platforms.
• Design cloud infrastructure capable of supporting AI workloads, including compute, storage, networking, and containerized services.
• Support the infrastructure requirements of AI applications across development, testing, and production environments.
• Collaborate with engineering teams to improve deployment reliability, scalability, and operational performance of AI-powered systems.
• Evaluate infrastructure technologies and tools that support evolving AI application requirements.

8. Technical Leadership & Team Development

• Provide technical leadership to DevOps engineers and guide implementation across projects.
• Establish engineering standards, infrastructure best practices, and operational procedures.
• Mentor team members on cloud architecture, automation, CI/CD, Kubernetes, and production operations.
• Lead technical discussions and make architecture decisions involving infrastructure and DevOps technologies.
• Collaborate with engineering, security, and product teams to align infrastructure capabilities with business requirements.
• Drive continuous improvement across DevOps processes, tools, and engineering practices.

Required Technical Skills & Experience

1. Cloud Platforms

• 10+ years of overall experience in DevOps, cloud infrastructure, or platform engineering.
• Strong hands-on expertise in at least one major cloud platform: AWS or Azure.
• Practical experience designing, deploying, and operating production-grade cloud infrastructure.

AWS: EC2, S3, IAM, VPC, EKS, Lambda, ECR, CloudWatch, and related infrastructure services.

Azure: Azure Virtual Machines, VNets, AKS, Azure DevOps, Azure Container Registry, Azure Monitor, Key Vault, and related infrastructure services.

Candidates do not need to be experts in both AWS and Azure. Deep expertise in either platform is the priority.

2. DevOps & CI/CD

• Strong experience designing and maintaining CI/CD pipelines.
• Hands-on experience with Azure DevOps, Jenkins, GitHub Actions, GitLab CI, or equivalent tools.
• Understanding of multi-stage pipelines, automated deployments, release approvals, and artifact management.
• Experience implementing deployment automation and rollback strategies.
• Strong understanding of Git workflows and version control practices.

3. Containers & Kubernetes

• Strong hands-on experience with Docker and Kubernetes.
• Practical experience managing EKS or AKS environments.
• Understanding of Kubernetes networking, scaling, storage, secrets, and workload management.
• Experience with Helm and container orchestration.
• Ability to troubleshoot production container and Kubernetes environments.

4. Infrastructure as Code & Scripting

• Strong experience with Terraform and Infrastructure as Code practices.
• Familiarity with CloudFormation, Bicep, ARM templates, or similar tools.
• Working knowledge of Python, Bash, or PowerShell for infrastructure automation.
• Strong understanding of Linux administration and system troubleshooting.

5. Monitoring & Reliability Engineering

• Experience implementing infrastructure and application monitoring.
• Familiarity with CloudWatch, Azure Monitor, Prometheus, Grafana, and centralized logging solutions.
• Understanding of incident management, root cause analysis, performance optimization, and system availability.
• Experience establishing alerting, operational dashboards, and reliability practices.

6. AI/ML Infrastructure Exposure

• Prior experience supporting AI/ML applications, Generative AI platforms, LLM applications, or AI-enabled products.
• Understanding of infrastructure requirements for deploying and operating AI-powered applications.
• Familiarity with containerized AI services, cloud-based model integrations, and scalable application environments.

Note: This role does not require specialized MLOps expertise or model development experience. Strong cloud and DevOps engineering fundamentals remain the primary requirement.

Preferred Skills

• Experience implementing GitOps workflows using Argo CD or similar tools.
• Experience with blue/green deployments, canary releases, and automated rollback mechanisms.
• Exposure to cloud security, enterprise networking, governance, and landing-zone architecture.
• Experience with cloud cost optimization and FinOps practices.
• Familiarity with AI/ML infrastructure and production GenAI applications.
• Experience with Python-based automation and infrastructure tooling.
• Relevant AWS, Azure, Kubernetes, or Terraform certifications.

What We're Looking For Beyond Skills

• Cloud Expertise: Deep technical specialization in AWS or Azure, with the ability to design and manage production infrastructure independently.
• Hands-on Engineering: Someone who actively builds, automates, troubleshoots, and improves infrastructure rather than focusing only on team management.
• Technical Ownership: Takes responsibility for infrastructure reliability, deployment quality, security, and operational performance.
• System Thinking: Understands how cloud infrastructure, applications, networking, databases, and deployment pipelines work together.
• Problem-Solving: Ability to diagnose complex production issues and implement long-term engineering solutions.
• Automation Mindset: Continuously identifies opportunities to eliminate manual work and improve operational efficiency.
• Technical Leadership: Can mentor engineers, establish best practices, and drive technical decisions.
• AI Readiness: Has practical exposure to supporting AI-powered applications and understands their infrastructure requirements.
• Collaboration: Works effectively with software engineering, AI/ML, security, and product teams.

Typical Technology Environment

AreaTechnologiesCloud PlatformsAWS, AzureCI/CDAzure DevOps, GitHub Actions, Jenkins, GitLab CIContainersDocker, Kubernetes, EKS, AKS, HelmInfrastructure as CodeTerraform, CloudFormation, Bicep, ARMGitOpsArgo CD, Git-based deployment workflowsMonitoring & ObservabilityCloudWatch, Azure Monitor, Prometheus, GrafanaAutomationPython, Bash, PowerShellOperating SystemsLinux, WindowsSecurityIAM, RBAC, Secrets Management, Network SecurityAI ExposureAI/ML Applications, GenAI, LLM Platforms, AI-enabled Products

What We Offer

• Competitive compensation aligned with experience and expertise.
• Coimbatore office-based work environment with hybrid flexibility.
• Opportunity to lead cloud infrastructure and DevOps engineering for global clients.
• Exposure to modern AWS/Azure, Kubernetes, automation, and AI engineering practices.
• Paid holidays and flexible time off.
• Medical insurance covering self and family, up to ₹4 lakh per person.
• Opportunities to influence infrastructure architecture and engineering practices.
• A culture that values clarity, integrity, ownership, and continuous growth.

Join Techjays

If you're passionate about building reliable cloud platforms, automating complex infrastructure, and leading DevOps engineering for modern AI-powered applications, we'd love to hear from you.

TECHJAYS

THE AI REIMAGINATION COMPANY

AI Quality Engineer

Position : AI Quality Engineer

Experience : 3–10 Years

Location : Coimbatore / Hybrid

Joining : Immediate / Within 30 Days

Primary SkillsManual & Functional Testing, AI/ML Application Testing, LLM Testing, Prompt Testing, Test Case Design, API Testing, Regression Testing, Defect Management

Preferred SkillsRAG Testing, Chatbot Testing, AI Response Evaluation, Selenium, Playwright, Cypress, Python, JavaScript, SQL, Postman, JIRA, BDD

About Techjays

At Techjays, we're helping businesses reimagine how they build, operate, and scale with AI at the core. We focus on developing intelligent, scalable, and production-grade AI solutions that solve real-world business challenges.

Our global team brings together experienced technology professionals from organizations such as Google, NetApp, ADP, Cognizant Consulting, and Capgemini. We work with global clients to build AI-powered applications, intelligent automation platforms, and enterprise software solutions.

We're looking for an AI Quality Engineer with strong functional testing expertise and prior hands-on experience testing AI/ML-powered applications.

This role goes beyond traditional software testing. You will be responsible for validating the quality, accuracy, reliability, and behaviour of AI-powered features, ensuring that intelligent applications perform consistently across different scenarios and real-world use cases.

The ideal candidate should understand both traditional QA methodologies and the unique testing challenges associated with AI systems, including non-deterministic outputs, prompt behaviour, hallucinations, response relevance, and edge-case validation.

Prior hands-on experience testing AI/ML-based products or applications is mandatory. Candidates with only traditional manual testing experience and no AI project exposure will not be a fit.

Key Responsibilities

1. AI Application & LLM Testing

• Perform functional and quality testing of AI-powered applications, LLM-based products, chatbots, and intelligent automation systems.
• Design test scenarios to validate AI-generated responses for accuracy, relevance, consistency, completeness, and contextual understanding.
• Test prompts, prompt variations, and conversational flows to identify unexpected outputs and behavioural inconsistencies.
• Evaluate AI responses for hallucinations, incorrect information, irrelevant answers, and context retention issues.
• Validate AI application behaviour across different user inputs, edge cases, and complex scenarios.
• Test RAG-based applications by validating document retrieval, response relevance, contextual accuracy, and source grounding.
• Evaluate AI-powered search, recommendation engines, and other intelligent product features.
• Collaborate with AI engineers and data science teams to define acceptance criteria and quality benchmarks.

2. Functional & Manual Testing

• Analyse business and technical requirements and convert them into comprehensive test scenarios and test cases.
• Execute functional, regression, integration, system, and user acceptance testing across web and mobile applications.
• Validate end-to-end application workflows, business logic, user interactions, and data processing.
• Identify functional gaps, unexpected behaviour, and usability issues.
• Perform exploratory testing to uncover defects that may not be covered by predefined test cases.
• Ensure application functionality remains stable across different releases and environments.
• Review requirements early in the development lifecycle to identify potential quality risks.

3. AI Quality Evaluation & Validation

• Develop structured testing approaches for non-deterministic AI outputs using behaviour-based, range-based, and scenario-based validation.
• Evaluate AI response quality against expected outcomes and predefined acceptance criteria.
• Validate prompt sensitivity, context handling, conversation memory, and multi-turn interactions.
• Identify failure patterns involving hallucinations, prompt injection, incorrect retrieval, and inconsistent responses.
• Test AI system performance across different input formats, languages, and user scenarios where applicable.
• Maintain test datasets and evaluation scenarios for repeatable AI quality assessment.
• Work with engineering teams to identify root causes of AI-related defects and verify fixes.

4. API & Integration Testing

• Perform manual API testing using Postman or similar tools.
• Validate API request and response structures, status codes, authentication, authorization, and error handling.
• Test integrations between AI services, backend systems, databases, and external APIs.
• Validate data flow between application components and identify integration issues.
• Test API behaviour under different input conditions, including invalid inputs and boundary cases.
• Verify API responses and ensure consistency between frontend and backend functionality.

5. Defect Management & Quality Reporting

• Identify, document, track, and manage defects throughout the testing lifecycle.
• Maintain detailed test cases, test execution reports, defect logs, and test documentation.
• Collaborate with developers to reproduce issues, analyse root causes, and validate fixes.
• Track test coverage, defect trends, and application quality metrics.
• Communicate release risks, unresolved defects, and testing status to relevant stakeholders.
• Participate in release readiness reviews and provide quality sign-off for assigned modules.

6. Automation & Continuous Improvement

• Identify repetitive test scenarios that can be automated to improve testing efficiency.
• Support automation initiatives using Selenium, Playwright, or Cypress.
• Work with developers to improve testability and integrate testing practices into CI/CD workflows.
• Explore AI-assisted testing tools and approaches to improve test coverage and efficiency.
• Continuously improve testing methodologies for both conventional software applications and AI-powered systems.

Required Skills & Experience

1. Functional & Manual QA

• 3–5 years of hands-on experience in manual and functional software testing.
• Strong understanding of software testing methodologies, SDLC, STLC, and defect management.
• Experience designing and executing test cases for functional, regression, integration, and end-to-end testing.
• Strong knowledge of Agile/Scrum methodologies and sprint-based QA processes.
• Experience testing web applications, APIs, and mobile applications.
• Ability to analyse requirements and identify functional gaps, edge cases, and potential risks.

2. Mandatory AI/ML Testing Experience

• Prior hands-on experience testing AI/ML-powered applications or products.
• Practical experience testing LLM-based applications, AI chatbots, conversational systems, or intelligent automation features.
• Understanding of prompt testing and evaluating AI-generated responses.
• Ability to validate AI outputs for accuracy, relevance, consistency, and contextual correctness.
• Experience identifying hallucinations, unexpected AI behaviour, and response-quality issues.
• Understanding of AI application workflows, model outputs, and the challenges associated with non-deterministic systems.
• Experience collaborating with AI/ML engineers or data science teams during testing and validation.

3. API & Integration Testing

• Hands-on experience with manual API testing using Postman.
• Understanding of REST APIs, JSON, request/response validation, authentication, and error handling.
• Experience validating integrations between frontend, backend, and external services.
• Basic understanding of database validation and SQL queries.

4. Testing Tools & Technologies

• Experience with JIRA and Confluence for defect tracking and test documentation.
• Familiarity with Postman, SQL, and browser developer tools.
• Understanding of test management and reporting practices.
• Basic knowledge of BDD frameworks such as Cucumber/Gherkin is an advantage.

Preferred Skills

• Experience testing RAG-based applications, including document retrieval and contextual response validation.
• Exposure to vector databases and semantic search testing.
• Familiarity with LangChain, LangGraph, LlamaIndex, or similar AI frameworks.
• Understanding of LLM evaluation frameworks and AI quality assessment methodologies.
• Experience with AI evaluation tools such as Ragas, DeepEval, or similar frameworks.
• Exposure to prompt injection, adversarial testing, and responsible AI validation.
• Working knowledge of Selenium, Playwright, or Cypress.
• Basic scripting knowledge in Python or JavaScript.
• Familiarity with CI/CD pipelines and automated testing practices.
• Exposure to cross-browser testing tools such as BrowserStack or Sauce Labs.

What We're Looking For Beyond Skills

• AI Testing Mindset: Understands that testing AI applications requires more than checking whether a feature works. Can evaluate response quality, accuracy, relevance, and behaviour.
• Analytical Thinking: Ability to identify unusual scenarios, inconsistent outputs, and hidden quality issues.
• Strong QA Fundamentals: Applies structured testing methodologies while adapting them to AI-powered applications.
• Attention to Detail: Documents defects clearly and identifies patterns in application and AI behaviour.
• Ownership: Takes responsibility for testing quality from requirement analysis through release validation.
• Collaboration: Works effectively with developers, AI engineers, product managers, and data science teams.
• Continuous Learning: Interested in exploring emerging AI technologies and evolving testing methodologies.
• Communication: Clearly communicates test results, defect impact, quality risks, and release readiness.

What We Offer

• Competitive compensation aligned with experience and expertise.
• Flexible work environment (Coimbatore office / Hybrid).
• Paid holidays and flexible time off.
• Medical insurance covering self and family, up to ₹4 lakh per person.
• Opportunity to work on real-world AI-powered products and enterprise applications.
• Hands-on exposure to LLMs, RAG systems, agentic AI, and modern AI engineering practices.
• Opportunities to develop expertise in AI quality engineering and automation testing.
• A collaborative, multicultural environment with opportunities for professional growth.
• A culture that values clarity, integrity, ownership, and continuous learning.

Join Techjays

If you're passionate about software quality and have hands-on experience validating AI-powered applications, we'd love to hear from you.

Join us in building reliable, intelligent, and production-ready AI systems.

AI Engineer

Experience: 2–4 Years

Employment Type: Full-Time

Work Mode: Coimbatore / Hybrid

About Techjays

Techjays is an AI Reimagination Company focused on building intelligent, scalable, and impactful software solutions. We help businesses solve complex challenges through AI, automation, and modern software engineering.

We are looking for an AI Engineer who is passionate about building AI-powered applications and integrating modern AI technologies into real-world products.

Key Responsibilities

• Design, develop, and deploy AI-powered applications using Python and modern AI frameworks.
• Build and implement LLM-based applications, including Retrieval-Augmented Generation (RAG) systems.
• Work with LLM APIs such as OpenAI, Gemini, and Anthropic.
• Develop AI agents and workflows using frameworks such as LangChain and LangGraph.
• Integrate vector databases and implement efficient embedding and semantic search solutions.
• Develop scalable backend services and REST APIs.
• Work with databases, data processing pipelines, and cloud-based services.
• Collaborate with frontend and backend teams to integrate AI capabilities into applications.
• Evaluate AI model performance, improve response accuracy, and optimize application performance.
• Debug, test, and maintain production-grade AI applications.

Required Skills

• 2–4 years of experience in software development, AI engineering, or a related field.
• Strong programming knowledge in Python.
• Hands-on experience with LLMs and Generative AI applications.
• Understanding of RAG architecture, embeddings, and semantic search.
• Experience with frameworks such as LangChain, LangGraph, or LlamaIndex.
• Knowledge of vector databases such as Pinecone, FAISS, ChromaDB, or Qdrant.
• Experience in building REST APIs using FastAPI or Flask.
• Good understanding of SQL and NoSQL databases.
• Familiarity with Git, Docker, and basic cloud services.
• Strong problem-solving and analytical skills.

Good to Have

• Experience building AI agents and multi-agent systems.
• Knowledge of React or other frontend frameworks.
• Exposure to AWS, Azure, or GCP.
• Understanding of model evaluation, prompt engineering, and fine-tuning.
• Experience deploying AI applications in production environments.

What We’re Looking For

• Someone who enjoys solving real-world problems using AI.
• Ability to take ownership of tasks and deliver solutions independently.
• Strong learning mindset and willingness to explore emerging AI technologies.
• Good communication and collaboration skills.

About

Asha Health is building an AI OS for outpatient care. It’s the year of AI agents, and startups selling AI agents to healthcare organizations will do great in this wave. While we’re rooting for them, we’re building what comes after. We're based in New York and backed by Y Combinator, General Catalyst, 186 Ventures, Reach Capital and many more. We raised an oversubscribed seed round from some of the best investors in Silicon Valley. Our team includes AI product leaders from companies like Google, physician executives from major health systems, and more.

About the Role

We're looking for a Product Manager, AI to join our team in our Bangalore office. With how AI models are evolving, we don't believe in traditional roles. Whereas in an old-school company you may write long PRDs and hand off to designers and engineering, and spend weeks in back and forths trying to get 1 feature approved, we operate completely differently. Here's what your day-to-day may look like:

• Instead of writing PRD's, you'll build prototypes.
• You'll be responsible for prioritizing which pain points to solve, outlining how we should solve them, and designing the user experience yourself as well (with the power of our AI design tools).
• At any given time, you may be using AI coding tools and AI design tools to parallel track prototypes for 5-10 large features.
• Rather than waiting weeks for approvals, features you prototype will be handed off to engineering and be shipped into production an average of 2-5 days.
• You will talk to customers and research the domain deeply - becoming an expert for the team on domain knowledge and product strategy.

Requirements

• Prior experience working as a Product Manager at a venture backed startup.
• Either (A) strong experience professionally as a software engineer, or (B) exceptional UX design skills. Must be multifaceted in one of these 2 ways.

Location - Bangalore / Pune 

Exp - 4 to 10 years 

Required

·      3–8 years of relevant experience in data science, AI engineering, or applied machine learning roles.

·      Bachelor’s or master’s degree in computer science, Mathematics, Engineering, or a related quantitative field.

·      System design: ability to design scalable, reliable, and maintainable systems, including service decomposition, APIs, caching, queues and event-driven architectures, and the trade-offs between latency, throughput, cost, and consistency.

·      Strong foundation in data structures and algorithms, with the ability to analyse time and space complexity and choose efficient approaches for large-scale data processing.

·      Experience building and operating data-intensive or data-driven applications, such as large-scale data pipelines, batch and streaming processing, or applications whose core features depend on high-volume data.

·      Strong hands-on experience in Python.

·      Solid foundation in machine learning, NLP, and statistical modeling, including data exploration and visualization.

·      Hands-on experience or projects involving LLMs, LangChain, LangGraph, RAG, or agentic AI systems.

·      Experience delivering AI/ML solutions into production environments.

·      Understanding of text processing and unstructured data.

·      Knowledge of software engineering best practices (TDD, refactoring, modular design, version control).

·      System design: ability to design scalable, reliable, and maintainable systems, including service decomposition, APIs, caching, queues and event-driven architectures, and the trade-offs between latency, throughput, cost, and consistency.

·      Strong foundation in data structures and algorithms, with the ability to analyze time and space complexity and choose efficient approaches for large-scale data processing.

·      Experience building and operating data-intensive or data-driven applications, such as large-scale data pipelines, batch and streaming processing, or applications whose core features depend on high-volume data.

·      Strong analytical, problem-solving, and communication skills.

·      Self-motivated, proactive, and delivery-oriented mindset.

Role Overview

We are looking for a strong Senior Python Engineer with hands-on AI/ML and Automation experience to join

our engineering team.

The engineer will work on high-scale backend systems, intelligent automation platforms, OCR/document

processing, AI-powered workflows, browser automation and integrations across multiple products.

This is not a role for someone whose AI experience is limited to calling LLM APIs. We need an engineer who

understands Python deeply and has built, deployed and maintained real production systems.

Experience Requirements

l Minimum 4 years of professional software development experience, primarily using Python.

l Minimum 2 years of practical hands-on experience in AI/ML, intelligent automation or closely related production

systems.

l Candidates with 4-6+ years of strong relevant experience are preferred.

l Strong production/backend engineering experience is essential.

Core Python & Backend Skills

l Python; FastAPI / Django / Flask; REST APIs and backend service development.

l Async programming and concurrency; multithreading / multiprocessing where appropriate.

l PostgreSQL / MySQL; Redis; background jobs and task queues such as Celery.

l WebSockets / real-time communication where required; authentication and authorization; API integrations.

l Docker; Linux; Git; logging, debugging and production troubleshooting.

l Ability to build fast, reliable and scalable Python services rather than only scripts.

AI / ML Requirements

l Machine Learning fundamentals; model training, evaluation and inference; data preprocessing and feature

engineering.

l Scikit-learn; PyTorch or TensorFlow; NLP.

l Embeddings, semantic search and vector databases.

l LLM integrations, prompt engineering, structured output and tool/function calling.

l RAG pipelines; AI agents / agentic workflows.

l OpenAI, Gemini, Claude or equivalent integrations; local/open-source model integration where appropriate.

l Understanding of model selection, accuracy, latency and cost trade-offs.

Automation Engineering

l Playwright; Puppeteer or equivalent browser automation frameworks; Selenium where appropriate.

l Headless browser and web workflow automation; form/repetitive task automation.

l Session/cookie management; file upload/download automation; API + browser hybrid automation.

l Retry and recovery mechanisms; scheduling and background execution.

l Queue-based automation workers; parallel/concurrent task processing.

Job Description

This is a remote position.

Want to build AI-powered products that real people use? We’re looking for hands-on Software Craftspeople who love TypeScript, care about clean code, and are excited about LLMs, agents and agentic workflows.

This role is ideal for engineers with 3–6 years of experience and a strong background in building scalable, production-grade software systems.

What You’ll Do

• Own features end to end, from design to production, on complex cross-functional projects.
• Build scalable backend systems and APIs in TypeScript using craftsmanship principles.
• Build AI applications and agentic workflows with OpenAI, Claude, Mastra and modern AI tooling.
• Build browser-based experiences, including Chrome Extensions, where needed.
• Spot risks early and drive solutions beyond your immediate scope.
• Raise the bar on code quality, testing and DevEx across the team.
• Work closely with clients, and mentor fellow engineers.

Requirements

What You’ll Bring

• A track record of owning production-grade systems, with strong hands-on TypeScript.
• Practical experience with LLM apps, AI agents and agentic frameworks (Mastra or similar), including extending agents with skills and tools.
• An understanding of Responsible AI: evaluation, reliability, safety and privacy.
• Experience building or integrating Chrome Extensions.
• Strong system design skills and solid engineering habits: TDD, CI/CD, refactoring, Agile/XP.
• Good knowledge of REST/gRPC APIs, relational databases and performance optimisation.

Nice to Have

• Python for production or AI/LLM systems
• LangChain, LlamaIndex, Agno, vector databases, AI eval and observability tools
• Docker, Kubernetes, Terraform
• React or another modern frontend framework

Working Hours

This role works with global clients, so you may sometimes need to join late-night calls (up to around 2 AM IST).

Benefits

Life at Incubyte  

We are a remote-first company with structured flexibility. Teams commit to shared rhythms during core hours, ensuring smooth collaboration while maintaining autonomy. Twice a year, we come together in person for a co-working sprint and once a year for a retreat - with all travel expenses covered.  

Our environment is built for crafters: pairing, refactoring, experimenting with AI, and pushing the boundaries of software excellence. We are all lifelong learners, and our work is our passion.  

Perks  

• Dedicated learning & development budget.  
• Sponsorship for conference talks.  
• Comprehensive medical & term insurance.  
• Employee-friendly leave policies.  
• Home Office fund  
• Medical Insurance  

AI Solution Architect

Experience: 12+ Years

Location: Coimbatore / Hybrid

Joining: Immediate / Within 30 Days

Primary Skills: Enterprise Architecture, Python, REST APIs, Microservices, Distributed Systems, Cloud (AWS/Azure/GCP), CI/CD, Docker, Kubernetes, Enterprise Data Architecture, Integration Patterns.

Preferred Skills: LLM Integrations, RAG Pipelines, AI Agents, Agentic Workflows, MCP (Model Context Protocol), Vector Databases, Prompt Engineering, LangChain/LlamaIndex, LLMOps, Multi-Agent Orchestration.

About the Role

At Techjays, we're helping companies reimagine how they build, operate, and scale with AI at the core. We focus on building secure, scalable, production-grade AI systems that solve real business problems and deliver measurable outcomes.

We're looking for an AI Solution Architect who can own enterprise-level solution architecture end-to-end. The ideal candidate combines deep technical expertise with the ability to understand complex business challenges, engage with prospective clients, and design compelling, scalable, AI-native solutions.

This is a senior technical role at the intersection of enterprise architecture, pre-sales, solutioning, and delivery governance. You'll collaborate with leadership, engineering teams, and clients to architect solutions spanning AI integrations, RAG pipelines, agentic workflows, cloud infrastructure, and enterprise platforms.

This role requires a strong technical background and current hands-on expertise. Candidates with purely pre-sales experience or non-technical solutioning backgrounds will not be a fit.

Key Responsibilities

• Own end-to-end enterprise architecture for AI-native platforms, defining high-level and low-level designs across backend systems, data platforms, and AI components.
• Lead solutioning for complex enterprise engagements, translating client requirements into technically sound, secure, scalable, and commercially viable architectures.
• Define reference architectures and design standards for LLM integrations, RAG pipelines, agentic workflows, MCP-based integrations, and enterprise data platforms.
• Partner with pre-sales and business development teams to prepare RFP responses, technical proposals, solution presentations, and architecture documents.
• Lead client discovery sessions and technical presentations, communicating architectural decisions and trade-offs to technical and executive stakeholders.
• Conduct architecture reviews and technical assessments to ensure scalability

Senior AI Engineer

Company: Techjays

Experience: 4–8 Years

Location: Coimbatore, Hybrid

Joining: Immediate or within 30 days preferred

About the Role

We are looking for a Senior AI Engineer with strong Python development skills and hands-on experience building and deploying AI-powered applications. The ideal candidate should have practical knowledge of LLMs, Retrieval-Augmented Generation (RAG), vector databases, and scalable backend systems.

You will work closely with engineering and product teams to design, develop, and deploy reliable AI solutions for real-world business problems.

Key Responsibilities

• Design, develop, and maintain scalable backend applications using Python and frameworks such as Django, Flask, or FastAPI.
• Build and integrate AI-powered applications using LLMs, RAG pipelines, and agentic AI workflows.
• Develop document processing, embedding generation, semantic search, and retrieval pipelines.
• Integrate LLM APIs and optimize prompts, response quality, latency, and cost.
• Work with vector databases and relational databases to build efficient data retrieval systems.
• Design and implement REST APIs, asynchronous processing, caching, and queuing mechanisms.
• Apply software engineering best practices, including design patterns, clean code, testing, and version control.
• Deploy and maintain applications on AWS or GCP using Docker and CI/CD pipelines.
• Monitor production systems, troubleshoot issues, and improve application performance and reliability.
• Collaborate with cross-functional teams to translate business requirements into practical AI solutions.
• Contribute to code reviews, technical documentation, and knowledge sharing within the engineering team.

Required Skills

• 4–8 years of experience in software development, with strong hands-on Python expertise.
• Strong understanding of data structures, algorithms, object-oriented programming, and design patterns.
• Experience building backend applications using Django, Flask, or FastAPI.
• Hands-on experience with LLM-based applications and API integrations.
• Practical experience implementing RAG pipelines, embeddings, and semantic search.
• Experience with vector databases such as Pinecone, Qdrant, Weaviate, or Chroma.
• Strong knowledge of SQL and relational databases such as PostgreSQL or MySQL.
• Experience with caching, message queues, asynchronous processing, and WebSockets.
• Familiarity with AWS or GCP, Docker, Git, and CI/CD pipelines.
• Understanding of API design, system architecture, application security, and performance optimization.
• Experience testing, debugging, and maintaining production-grade applications.

Preferred Skills

• Experience building agentic AI applications and multi-agent workflows.
• Familiarity with LangChain, LangGraph, LlamaIndex, or similar frameworks.
• Knowledge of Model Context Protocol (MCP) and tool-calling mechanisms.
• Experience with LLM evaluation, hallucination reduction, and output quality monitoring.
• Familiarity with fine-tuning, model selection, and inference optimization.
• Experience with LLMOps, AI observability, and production monitoring.
• Knowledge of Kubernetes and microservices architecture.

What We’re Looking For

• Strong problem-solving and analytical skills.
• Ability to take ownership of features from development through deployment.
• Practical understanding of how to build reliable AI applications beyond prototypes.
• Ability to make sound technical decisions and explain architectural trade-offs.
• Good communication and collaboration skills.
• Willingness to learn, experiment, and work on challenging AI engineering problems.

Lead AI Engineer

Experience: 8+ Years

Location: Coimbatore / Hybrid

Joining: Immediate or within 30 days

About Techjays

At Techjays, we help businesses reimagine how they build, operate, and scale through AI. We focus on developing secure, scalable, production-grade AI solutions that solve real business problems and deliver measurable outcomes.

Our engineering team brings experience from organizations such as Google, NetApp, ADP, Cognizant Consulting, and Capgemini. We combine strong engineering fundamentals with an execution-focused mindset to build advanced AI systems for global clients.

About the Role

We are looking for a Lead AI Engineer to drive the architecture and development of scalable backend systems and AI-powered applications.

In this role, you will lead the technical design and implementation of Python-based systems, oversee LLM integrations and RAG pipelines, and develop agentic AI workflows for production environments. You will take ownership of complex engineering challenges, establish coding and architectural standards, and mentor engineers to deliver reliable, maintainable, and high-performing solutions.

This is a hands-on technical leadership role for someone who can translate complex requirements into practical engineering solutions and take them from design to production.

Key Responsibilities

1. Backend Engineering & System Architecture

• Design and develop scalable, secure backend systems using Python and frameworks such as Django or Flask.
• Architect RESTful APIs, WebSocket services, and distributed systems that support high-performance applications.
• Apply design patterns, algorithms, and data structures to solve complex engineering challenges.
• Design efficient database schemas, caching strategies, and data access patterns for scalable applications.
• Establish engineering standards for code quality, testing, maintainability, and system performance.

2. AI Engineering & LLM Integration

• Architect and implement LLM-powered applications, retrieval-augmented generation (RAG) pipelines, and agentic AI workflows.
• Develop solutions using vector databases, embeddings, semantic search, and prompt engineering.
• Build and optimize multi-agent systems, orchestration workflows, and tool integrations using frameworks such as LangChain and LlamaIndex.
• Implement Model Context Protocol (MCP) integrations where appropriate to connect AI systems with external tools and data sources.
• Evaluate model fine-tuning approaches and other techniques to improve AI performance where required.
• Establish LLMOps practices covering evaluation, observability, quality monitoring, and cost and latency optimization.

3. Cloud Infrastructure & Deployment

• Design and deploy cloud-native applications using AWS and GCP services.
• Build and maintain CI/CD pipelines using Jenkins, GitLab CI, GitHub Actions, or similar tools.
• Containerize applications using Docker and support deployment and operations in Linux environments.
• Implement reliable asynchronous processing and messaging using queuing systems.
• Improve system availability, scalability, security, and deployment reliability across production environments.

4. Technical Leadership & Engineering Excellence

• Own technical decisions across complex backend and AI engineering initiatives.
• Guide engineers in architecture, implementation, debugging, code reviews, and engineering best practices.
• Identify performance bottlenecks and drive improvements in application reliability and scalability.
• Collaborate with product managers, frontend engineers, data scientists, and other stakeholders to deliver effective solutions.
• Evaluate emerging AI technologies, frameworks, and tools, adopting them when they provide meaningful technical or business value.
• Take ownership of features from technical design through implementation, deployment, and production support.

Required Technical Skills

Backend Development

• Strong Python programming expertise.
• Experience with Django, Flask, RESTful APIs, and WebSockets.
• Strong understanding of object-oriented programming, design patterns, algorithms, and data structures.

Databases & Performance

• Experience with PostgreSQL, MySQL, MongoDB, or equivalent database technologies.
• Strong understanding of relational database design, query optimization, and performance tuning.
• Experience implementing caching strategies and asynchronous processing.

Cloud & DevOps

• Hands-on experience with AWS and/or GCP.
• Experience with Git, Docker, Linux, and CI/CD pipelines.
• Familiarity with queuing systems and distributed application architectures.

System Design

• Ability to design secure, scalable, and maintainable backend systems.
• Experience making architecture decisions involving performance, reliability, scalability, and operational complexity.

Preferred AI/ML Skills

• Large Language Models (LLMs) and prompt engineering.
• Retrieval-Augmented Generation (RAG) architecture.
• Vector databases such as Pinecone, ChromaDB, or equivalent.
• Embeddings, semantic search, and retrieval optimization.
• Agentic AI workflows and multi-agent orchestration.
• Model Context Protocol (MCP) and tool integrations.
• LangChain, LlamaIndex, or similar frameworks.
• Model fine-tuning and LLMOps practices.
• AI evaluation frameworks, observability, and production quality monitoring.
• Experience optimizing inference costs, response latency, and AI application performance.

What We're Looking For

• Strong engineering fundamentals: You can solve complex technical problems and design maintainable systems.
• Hands-on ownership: You take responsibility for solutions from concept through production.
• System-level thinking: You understand how architecture, performance, security, and scalability work together.
• Practical AI expertise: You can build and deploy AI-powered applications beyond prototypes and proof of concepts.
• Technical leadership: You guide engineers, improve code quality, and establish sound engineering practices.
• Structured problem-solving: You make thoughtful technical decisions in ambiguous and fast-moving environments.
• Clear communication: You collaborate effectively across engineering and business teams.
• Continuous improvement: You stay current with evolving AI technologies and apply them where they create value.
• 
  

What We Offer

• Competitive compensation.
• Flexible work environment with Coimbatore office and hybrid options.
• Paid holidays and flexible time off.
• Medical insurance for self and family, with coverage of up to ₹4 lakhs per person.
• Opportunities to architect and build production-grade AI systems used by real customers.
• Exposure to global clients and technically challenging projects.
• A culture that values ownership, clarity, integrity, and continuous learning.

Director of Engineering (AI Solutions & Delivery)

About the Role

We are looking for a Director of Engineering to lead engineering execution and delivery across our enterprise AI solutions. This role combines strong engineering leadership with operational discipline, ensuring AI products move from technical design to production with predictable timelines, high quality, and reliable performance.

You will lead Engineering Managers and Tech Leads, oversee multiple engineering teams, and drive delivery excellence across AI-powered applications and platforms. The focus is on execution, technical quality, and organizational accountability, ensuring teams deliver scalable, production-ready AI systems without compromising reliability or engineering standards.

Key Responsibilities

1. Engineering Delivery & Execution

• Own engineering delivery schedules, translating product roadmaps into achievable sprint plans and release milestones.
• Establish measurable delivery targets, aiming for at least 85% on-time delivery across engineering teams.
• Identify and resolve cross-team dependencies, technical bottlenecks, and resource constraints before they affect delivery.
• Drive engineering process improvements across Agile development, CI/CD, automated testing, and release management.
• Monitor delivery metrics, sprint commitments, and release readiness to maintain predictable execution.

2. AI Quality, Evaluation & Governance

• Establish automated AI evaluation pipelines to measure hallucinations, relevance, groundedness, and contextual accuracy before production releases.
• Define quality benchmarks and evaluation criteria for LLM-powered applications and AI-driven workflows.
• Implement safety mechanisms, validation filters, circuit breakers, and human-in-the-loop fallbacks to manage unpredictable AI outputs.
• Oversee RAG pipelines, vector databases, data ingestion, and retrieval mechanisms to maintain accurate, reliable, and compliant context.
• Reduce production AI quality regressions through continuous evaluation, monitoring, and feedback loops.

3. Architecture, Scalability & Reliability

• Oversee the architecture of distributed systems and cloud-native applications to support scalability, availability, and performance.
• Drive reliability targets, including 99.9% uptime and low time-to-first-token (TTFT) latency for applicable AI applications.
• Partner with Staff and Principal Engineers to design resilient systems, including fallback mechanisms for model API failures, timeouts, and rate limits.
• Establish engineering standards for code reviews, observability, automated integration testing, and security compliance.
• Ensure production systems meet defined service-level objectives (SLOs) and performance benchmarks.

4. Engineering Leadership & Team Development

• Lead and develop Engineering Managers and Tech Leads, establishing clear ownership, accountability, and delivery expectations.
• Build a high-performance engineering culture focused on technical excellence, collaboration, and continuous improvement.
• Partner with Talent Acquisition to attract, assess, and hire strong software engineering and AI talent.
• Align engineering resources with business priorities, delivery commitments, and technical requirements.
• Address performance and execution challenges while maintaining team engagement and engineering quality.

Success Metrics: First 90 Days

First 30 Days

• Assess existing engineering workflows, delivery pipelines, and release processes.
• Establish baseline AI evaluation criteria and identify gaps in production quality.
• Take ownership of engineering delivery across teams and align expectations with Engineering Managers and Tech Leads.

First 60 Days

• Implement automated AI evaluation frameworks and establish measurable quality benchmarks.
• Improve cross-team coordination and resolve key delivery dependencies.
• Establish consistent sprint planning, release cadences, and delivery reporting.

First 90 Days

• Achieve at least 85% sprint commitment completion.
• Demonstrate measurable reductions in production AI quality regressions.
• Improve system reliability and stabilize latency against defined performance targets.
• Establish clear accountability and predictable delivery practices across engineering teams.

Qualifications & Requirements

• Experience: 14+ years in software engineering, including at least 5 years managing Engineering Managers or Tech Leads in enterprise or high-growth environments.
• AI/ML Expertise: Hands-on experience delivering AI-powered systems involving LLMs, RAG architectures, vector databases, prompt engineering, or model fine-tuning workflows.
• Engineering Delivery: Proven ability to lead multiple engineering teams and deliver complex technical initiatives from design through production launch.
• System Architecture: Experience with distributed systems, cloud-native backend infrastructure, and scalable APIs across AWS, GCP, or Azure.
• AI Quality & Reliability: Understanding of AI evaluation frameworks, production monitoring, hallucination mitigation, guardrails, and system reliability.
• Delivery Management: Strong experience with Agile methodologies, CI/CD, release planning, and engineering performance metrics.
• Leadership: Ability to establish accountability, manage competing priorities, and deliver against ambitious deadlines without compromising quality or team morale.

What Success Looks Like

The successful candidate will establish predictable engineering delivery, improve the quality and reliability of production AI systems, and build a culture of ownership across engineering teams. They will combine technical judgment with execution-focused leadership to ensure AI solutions are delivered on schedule, operate reliably, and meet enterprise expectations.

If you are passionate about building high-performing engineering teams and delivering enterprise-grade AI solutions at scale, we would like to hear from you.

AI Project Manager

About Techjays

At Techjays, we are driving the future of artificial intelligence with a bold mission to empower businesses worldwide by helping them build AI solutions that transform industries. As an established leader in the AI space, we combine deep expertise with a collaborative, agile approach to deliver impactful technology that drives meaningful change. Our global team consists of professionals from leading companies such as Google, Akamai, NetApp, ADP, and Cognizant.

Role Overview

We are seeking a seasoned Project Manager to oversee the successful delivery of complex AI-driven projects. You will be responsible for bridging organizational goals with cross-functional execution, ensuring that our technical teams deliver high-quality solutions on schedule and within budget.

Key Recruitment Details

• Experience Required: 8 + Years (Minimum 6+ years in end-to-end project management)
• Work Location: Coimbatore / Hybrid
• Target Joining Date: (ASAP / Within 30 days)

Must-Have Qualifications

• Proven Execution: 6+ years of experience managing the complete lifecycle of enterprise-grade software projects.
• Agile Expertise: Advanced proficiency in Agile/Scrum methodologies, with a track record of facilitating sprint planning, stand-ups, and retrospectives.
• Technical Proficiency: Mastery of project management tools including Jira, MS Project, or Trello.
• Strategic Planning: Demonstrated experience in resource allocation, risk mitigation, and contingency planning.
• AI Enthusiasm: Experience leveraging AI tools in project management or a demonstrated passion for adopting AI technologies to optimize workflows.
• Stakeholder Management: Exceptional communication skills for managing both internal cross-functional teams and external client relationships.

Roles & Responsibilities

• Project Governance: Plan, execute, and monitor projects to ensure alignment with client expectations and organizational benchmarks.
• Team Leadership: Facilitate high-performing Agile environments, fostering a culture of collaboration, innovation, and technical ownership.
• Risk & Budget Management: Identify potential bottlenecks early, implement mitigation strategies, and manage project budgets to ensure optimal resource utilization.
• Reporting & Transparency: Track project progress using modern metrics, preparing detailed reports and presentations for senior management.
• Continuous Improvement: Analyze project outcomes to implement best practices and drive operational discipline across the engineering organization.
• Mentorship: Elevate team members through active support and guidance, ensuring professional growth within the team.

Success Milestones

Timeline

Expectations

First 30 Days

Audit active project pipelines, establish stakeholder relationships, and assume management of ongoing sprint cycles.

First 60 Days

Optimize resource allocation workflows, streamline cross-team communication, and implement improved risk-tracking mechanisms.

First 90 Days

Achieve >85% sprint commitment completion rate and stabilize project delivery predictability across assigned teams.

What Techjays Offers

• Competitive Compensation: Best-in-class packages structured to reflect experience and impact.
• Health & Wellness: Medical insurance covering self and family up to ₹4 lakhs per person.
• Flexibility: A trust-based time-off policy and a flexible hybrid work model.
• Environment: A casual work culture with a diverse, multicultural team that respects ideas regardless of designation.
• Growth: Meaningful professional development in an innovation-driven culture.

Job Details

Position Title: AI Evangelist

Role Purpose

We are seeking a highly experienced AI Evangelist & Core AI Engineer who combines deep technical expertise in Artificial Intelligence with the ability to influence, educate, demonstrate, and accelerate AI adoption across the enterprise.

The role requires deep understanding of AI, Machine Learning, Deep Learning, Generative AI, Large Language Models, Agentic AI, AI engineering, and modern software development practices, combined with significant hands-on experience implementing scalable AI applications in complex enterprise environments.

Key Responsibilities

1. Core AI Engineering & Architecture

• Design, develop, and implement enterprise-grade AI and Generative AI applications.
• Build scalable applications using LLMs, multimodal models, AI agents, RAG, vector databases, knowledge graphs, APIs, and enterprise data platforms.
• Architect AI solutions capable of supporting enterprise-scale workloads with appropriate considerations for:
• Scalability
• Reliability
• Security
• Performance
• Observability
• Cost optimization
• Governance
• Develop and implement advanced Retrieval-Augmented Generation (RAG) architectures including hybrid search, reranking, metadata filtering, semantic retrieval, and knowledge grounding.
• Build multi-agent and agentic AI applications capable of reasoning, tool usage, workflow execution, orchestration, and enterprise system integration.
• Design AI applications integrating structured and unstructured enterprise information.
• Evaluate architecture choices between commercial models, open-source models, small language models, domain-specific models, and hosted AI platforms.
• Implement model routing, prompt orchestration, caching, guardrails, evaluation pipelines, and fallback strategies.
• Work closely with cloud, platform, security, enterprise architecture, DevOps, and application engineering teams.

2. Deep AI / ML / DL Expertise

The candidate should have strong conceptual and practical understanding across the modern AI technology landscape, including:

• Artificial Intelligence /Machine Learning/ Deep Learning/ Neural Networks /LLM/SLM/RAG/Graph RAG / MLOps / LLMOps / GenAIOps

3. Generative AI & LLM Engineering

• Build production-grade applications utilizing leading commercial and open-source LLM ecosystems.
• Design scalable LLM platforms supporting multiple enterprise applications and use cases.
• Develop reusable LLM services, APIs, components, agent frameworks, and reference architectures.

4. AI Agents & Automation

• Design and implement AI agents and agentic workflows that automate complex business and engineering processes.
• Build agents capable of interacting with enterprise applications, APIs, databases, documents, development environments, and workflow platforms.
• Evaluate emerging agent architectures and orchestration frameworks pragmatically.
• Develop reusable patterns for:
• Single-agent systems
• Multi-agent systems
• Human-in-the-loop workflows
• Autonomous workflows
• Tool-calling agents
• Coding agents
• Enterprise knowledge agents
• Establish appropriate controls for AI agent identity, permissions, auditability, security, and human oversight.

5. AI-Enabled Software Engineering

Drive adoption of AI throughout the Software Development Life Cycle.

Company: Wissen Technology

Position: Python AI Engineer

Experience: 4-6 Years

Location: Bengaluru

Employment Type: Full-time

About Wissen Technology

Wissen Technology is a global technology services company focused on delivering innovative software engineering, data, and technology solutions to leading enterprises. The company works with clients across industries to build scalable, high-performance technology platforms and solve complex business and technology challenges.

With a strong focus on engineering excellence, innovation, and collaboration, Wissen Technology brings together skilled technology professionals across areas such as software engineering, data engineering, cloud, analytics, and digital transformation.

At Wissen Technology, employees have the opportunity to work on challenging technology projects, collaborate with experienced engineering teams, and contribute to solutions that create measurable business impact.

Job Summary

Wissen Technology is hiring a Python AI Engineer for a team building a finance application in global financial services. You will use Python to build LLM-powered applications and AI agents that help finance and operations users find, understand, and act on their data. The ideal candidate should have strong expertise in Core Python, data handling, and AI/LLM engineering and hands-on experience in developing AI-powered applications using Agentic AI frameworks such as LangChain and LangGraph, along with Retrieval-Augmented Generation (RAG).

Job Responsibilities:

• Develop and maintain applications using Core Python.
• Design and develop scalable backend services using FastAPI.
• Build and integrate RESTful APIs for application development.
• Work with NumPy and Pandas for data manipulation and processing.
• Develop AI-powered applications using Generative AI and LLM technologies.
• Implement RAG-based solutions for intelligent document retrieval and information extraction.
• Work with LangChain for LLM orchestration and application development.
• Develop document processing pipelines, including text extraction, parsing, chunking, and data extraction.
• Integrate LLM APIs into existing applications and workflows.
• Optimise application performance, scalability, and reliability.
• Collaborate with cross-functional teams to deliver AI-driven solutions.

Required Skills

• Strong programming experience in Core Python.
• Hands-on experience with FastAPI.
• Good knowledge of NumPy and Pandas.
• Experience in REST API development and integration.
• Practical experience with LangChain.
• Strong understanding of Retrieval-Augmented Generation (RAG).
• Knowledge of AI, Generative AI, and Large Language Models (LLMs).
• Experience in document processing and data extraction.

Job Title: Engineering Manager

Location- Delhi

Job type: Full time, On site

About Us: TIMBLE is leading Authentication Company, delivering cutting edge technology and alternate data analysis for Identity management, Onboarding & Verification and Business Intelligence. We provide solutions across three verticals

1. BFSI Solutions

2. KYC and background check Solutions

3.AI Solutions

Role Overview

As an Engineering Manager at Timble AI, you will manage, mentor, and scale our core engineering teams (including Backend, Frontend, and AI/ML divisions). You will remain highly technical, contributing to architecture decisions and system design, while taking full ownership of project delivery timelines, agile sprints, and team performance metrics.

Key Responsibilities

1. People Leadership & Mentorship: Manage and grow a cross-functional team of software engineers (SDE-1 to SDE-3). Conduct regular 1-on-1s, drive career growth paths, and foster an innovative, high-ownership engineering culture.
2. Delivery & Agile Project Management: Own the engineering sprint cycles. Work closely with Product Managers to break down roadmaps into execution goals, manage dependencies, and ensure high-velocity, predictable delivery.
3. System Design & Architecture: Provide technical governance and direction. Collaborate on core system architecture, design reviews, and ensure codebases remain clean, scalable, and modular.
4.  Engineering Excellence: Define and monitor key performance indicators (KPIs) for the engineering team, including code quality, test coverage, uptime, and system performance.
5. Hiring & Scaling: Actively partner with the talent acquisition team to identify, interview, and onboard top-tier engineering talent to help build our core verticals.

Required Skills & Qualifications

1. Experience: 5+ years of core software engineering experience, with at least 1–2 years of experience in an engineering management, tech lead, or team leadership role.
2. Technical Roots: Strong foundational background in backend systems, distributed architectures, or AI integration. Prior hands-on experience with Python/Django ecosystems, microservices, cloud infra (AWS/GCP), or heavy automation systems is highly valued.
3. Agile Mastery: Deep familiarity with Agile/Scrum development methodologies, sprint planning tools, and CI/CD pipelines.
4.  Communication: Exceptional interpersonal and cross-functional communication skills, with a track record of translating complex technical visions into clear execution steps.
5.  Education: B.Tech / M.Tech in Computer Science, Information Technology, or a related technical discipline from a reputed institute.

Learn more about us at: https://timbleglance.com

This skill is mandatory. Candidates must know this:

- TypeScript/JavaScript

- Rust 

- AI coding (good to have)

Senior Content Marketer

SERP Forge  |  Full-time  |  Remote |  Reports to the Marketing & Growth Lead

About SERP Forge

SERP Forge is a B2B SaaS marketing agency helping software companies grow through search and performance-led marketing. We are hiring a senior, hands-on content marketer to make our content a reliable source of discovery, trust, and qualified demand.

The role

You will own content from the business brief through research, writing, publishing, distribution, measurement, and improvement. The work spans SEO articles, website and service pages, landing pages, Google and LinkedIn ad copy, and thought leadership for SERP Forge and its leaders. You will also steward one clear brand voice across these channels.

This is a senior individual-contributor role for someone who writes exceptionally well, understands how content contributes to growth, and can operate without a manager creating step-by-step SOPs or reviewing every draft. You will build practical AI-assisted workflows that increase useful output while keeping the work accurate, distinctive, and human.

What you will own

Content strategy and SEO performance

• Turn business priorities, customer needs, and SEO opportunities into a focused content plan. Prioritize work by audience intent, search potential, campaign timing, and contribution to pipeline.
• Research, write, edit, publish, and refresh SEO-friendly articles and website pages. Apply search intent, keyword research, on-page SEO, internal linking, and clear conversion paths.
• Partner with the SEO and development teams to confirm page requirements, publishing details, technical dependencies, and performance fixes. Track visibility and traffic for the pages you own, then act on the findings.

Website, campaign, and social copy

• Write and improve service pages, campaign landing pages, comparison or solution pages, and other website copy that explains our offer clearly and moves the right buyer toward action.
• Develop Google Ads and LinkedIn Ads copy with the paid media owner. Create message variations, align ads with their landing pages, and use test results to improve click-through, conversion, and lead quality.
• Create thought leadership posts and campaign content for SERP Forge and company leaders. Interview subject-matter experts and turn their experience into useful, specific points of view.
• Adapt the format and tone to each channel while keeping our positioning, terminology, and brand voice consistent.

AI-enabled content workflows

• Design and operate a repeatable content workflow using AI tools and automation. The workflow should support research, briefs, drafting, editing, repurposing, quality checks, publishing, and performance feedback.
• Build meaningful systems beyond one-off prompts. Use tools such as LLMs, automation platforms, CMS integrations, and analytics where they improve speed or consistency.
• Keep human editorial judgment in the process. Verify claims and sources, protect confidential information, check originality and brand voice, and prevent generic or inaccurate content from being published.
• Document the workflow clearly enough to maintain and improve it, and report what the system changes in quality, cycle time, and output.

Independent ownership and collaboration

• Gather requirements directly from management, SEO, paid media, sales, and development. Clarify the audience, business goal, evidence, CTA, dependencies, and success measure before work begins.
• Own research, writing, editing, fact-checking, SEO checks, and final quality assurance. Deliver work that is publish-ready without line-by-line supervision.
• Plan and communicate independently, raise blockers early, manage deadlines, and recommend the next action when results are below target. Seek expert review when a claim or technical detail needs validation.

Performance reporting

• Set a baseline and agree quarterly targets for priority content and campaigns with the Marketing & Growth Lead.
• Report monthly on organic visibility and clicks, rankings for priority topics, traffic to owned pages, and conversions such as qualified leads, demo or contact requests, SQLs, and content-influenced pipeline where tracking supports it.
• For paid and campaign content, review the agreed measures with the channel owner, such as ad engagement, landing-page conversion rate, cost per qualified lead, and lead quality. Recommend and run copy or page experiments.
• Separate what the content changed from dependencies such as technical implementation, media budget, audience targeting, offer, or sales follow-up. Make the dependencies visible and keep ownership of the analysis, learning, and content improvements.

How success will be measured

The role is evaluated on business performance and the quality of the operating system, not on a content-count quota alone. Targets will be agreed from current baselines and business priorities. Core measures include:

• Growth in search visibility, rankings, and qualified organic traffic for priority pages and topics.
• Conversions from owned content and landing pages, including qualified leads and SQLs; content-influenced pipeline where attribution is available.
• Improvement in paid and campaign copy performance through structured testing with the channel owner.
• Reliable, accurate content delivery and a consistent brand voice across the website, advertising, and social channels.
• A repeatable AI-assisted workflow that improves production efficiency without lowering editorial quality.

What you bring

• At least five years of experience in content marketing, SEO content, editorial, or content-led growth, ideally in B2B SaaS or technology.
• A strong portfolio across SEO articles, website or landing pages, ad copy, and thought leadership. Your samples should show that you can change format and tone without losing clarity or voice.
• Evidence that your content improved rankings, organic traffic, conversions, or pipeline. You can explain your contribution, starting point, measurement window, outcome, and what you changed next.
• Strong command of written English and the ability to simplify complex services and technical ideas without making unsupported claims.
• Working knowledge of search intent, keyword research, on-page SEO, Google Search Console, Google Analytics 4, and an SEO research platform such as Ahrefs or Semrush.
• Demonstrated ability to build and run an AI-enabled content workflow with automation, quality controls, and human editorial review. You can show the stages, tools, checks, and practical result.
• The judgment and discipline to plan, write, edit, QA, publish, and report independently in a fast-moving environment.

Useful additional experience

• Experience in a SaaS agency or in-house SaaS marketing team, particularly with SEO, link building, or demand generation.
• Experience improving conversion paths, running landing-page tests, or working with Google Ads and LinkedIn Ads teams.
• Experience ghostwriting for executives, using CMS platforms such as WordPress, or developing content for AI answer engines as well as traditional search.

What you should be able to show

Please include a portfolio with at least three relevant samples and one short case study showing the goal, your role, timeframe, result, and how you measured it. Also include an example or simple diagram of an AI-assisted content workflow you built or operated, including its human quality checks. You may anonymize confidential company or client details.

First 90 days

• Establish a baseline for current priority pages and content performance, then agree the first set of outcome targets with the Marketing & Growth Lead.
• Deliver and improve priority website, SEO, campaign, and thought leadership content in collaboration with the relevant teams.
• Put a documented AI-assisted content workflow into regular use, with clear quality checks and performance feedback.
• Present a concise monthly view of results, learnings, dependencies, and the next content priorities.

Junior PHP/Laravel developer - Education ERP

Experience: 1.5-3 Years

Location: Remote

We are looking for a Junior PHP/Laravel Developer with hands-on experience in Core PHP, Laravel, and MySQL. The candidate will work on Education ERP/EdTech applications, developing new features, fixing bugs, handling databases, and supporting existing applications.

Key Responsibilities:

Develop and maintain web applications using Core PHP and Laravel.

Write and optimize MySQL/SQL queries and perform database operations.

Develop and maintain ERP/EdTech modules and features.

Create and integrate REST APIs and third-party services.

Debug and resolve application issues and bugs.

Understand existing codebases, database structures, and data flow.

Follow coding standards, Git practices, and development best practices.

Coordinate with senior developers to complete assigned tasks on time.

Required Skills

• Core PHP & Laravel
• MySQL / SQL
• Database relationships, joins, CRUD, and query optimization
• HTML, CSS, JavaScript & jQuery
• REST APIs and API integration
• Basic Git/version control
• Good debugging and problem-solving skills
• Ability to understand and work with an existing codebase
• Preferred Experience

Experience with any of the following will be an advantage:

• Education ERP / EdTech
• LMS / School / College Management Systems
• Admission & Student Management
• Fee Management
• Examination Modules
• HRMS
• Finance Modules Qualifications

B.Tech/B.E. (CS/IT), BCA, MCA, or equivalent qualification with relevant development experience.

What We Offer:

• Remote Work
• Opportunity to work on Education ERP products
• Learning and professional growth opportunities
• Exposure to real-world enterprise applications
• Supportive development environment

About the Role

Antier Solutions is looking for a technically strong AI Solution Architect to drive the architecture, design, and technical execution of AI-powered solutions.

The role requires a combination of deep technical expertise, architectural ownership, and the ability to guide engineering teams in building scalable, production-ready AI systems. The individual will evaluate business problems, define technical approaches, make architecture decisions, and work closely with developers and stakeholders to translate ideas into working solutions.

This is a hands-on architecture and technical leadership role, not one limited to documentation, project coordination, or pre-sales presentations.

Key Responsibilities

1. AI Architecture & Solution Design

• Design end-to-end architectures for AI, Generative AI, LLM-based applications, and agentic AI systems.
• Evaluate and select appropriate models, frameworks, orchestration approaches, and technology stacks.
• Design solutions involving RAG, AI agents, workflow automation, APIs, databases, and enterprise integrations.
• Define architecture standards covering scalability, security, performance, maintainability, and deployment.
• Evaluate technical feasibility, identify risks, and recommend practical implementation approaches.

2. Technical Leadership & Implementation

• Provide architectural direction and technical guidance to AI engineers and developers.
• Review proposed designs and implementation approaches, identifying technical gaps and potential bottlenecks.
• Establish reusable architecture patterns, development standards, and engineering best practices.
• Troubleshoot complex technical challenges and contribute hands-on where necessary.
• Guide teams in adopting AI-assisted development and agentic workflows where they improve engineering productivity.

3. Production Readiness & Quality

• Design solutions with appropriate authentication, access controls, logging, monitoring, testing, and evaluation mechanisms.
• Address AI-specific challenges such as hallucinations, retrieval quality, model selection, latency, reliability, and inference costs.
• Define appropriate human oversight and validation mechanisms for sensitive or consequential workflows.
• Guide deployment decisions across suitable cloud, on-premise, and hybrid environments.

4. Business Alignment & Delivery Ownership

• Understand business requirements and translate them into implementable technical solutions.
• Work with stakeholders to establish scope, dependencies, estimates, resource requirements, and delivery milestones.
• Collaborate with engineering and delivery teams to move solutions from proof of concept to production.
• Balance rapid execution with architectural quality, maintainability, and commercial feasibility.
• Communicate technical decisions, risks, and trade-offs clearly to business and technical stakeholders.

Required Skills & Experience

• B.Tech, BE, MCA, MSc, or equivalent technical qualification in Computer Science, IT, Data Science, or a related discipline.
• 8+ years of overall experience in software engineering, AI engineering, solution architecture, or related technical roles.
• Strong hands-on experience building AI/ML or Generative AI applications, with demonstrated responsibility for architecture and implementation decisions.
• Strong understanding of LLMs, RAG pipelines, agentic AI systems, tool calling, orchestration, and AI-driven automation.
• Experience with Python and relevant AI frameworks, libraries, and integration technologies.
• Strong understanding of APIs, databases, data pipelines, distributed systems, and application architecture.
• Experience evaluating AI solutions for accuracy, reliability, performance, security, and cost.
• Ability to guide developers, review technical approaches, resolve complex problems, and establish reusable engineering practices.
• Experience deploying or supporting AI applications in production environments.
• Strong analytical, communication, and technical decision-making skills.

Preferred Qualifications

• Experience architecting multi-agent systems or complex AI automation workflows.
• Exposure to cloud platforms, containerization, CI/CD, observability, and scalable AI infrastructure.
• Experience mentoring engineering teams and introducing new AI development practices.
• Experience with enterprise AI deployments, international clients, or technically complex business environments.

Ideal Candidate Profile

• We are looking for an individual who can independently own technical architecture, guide engineering teams, and make sound implementation decisions. The candidate should combine hands-on AI expertise with the ability to turn business requirements into scalable, production-ready solutions.
• Candidates whose experience is limited to AI research, business analysis, project coordination, or pre-sales documentation without meaningful technical implementation and architecture ownership may not be suitable.

🚀 WE ARE HIRING | JAVA FULL STACK DEVELOPER (React + Kafka + AWS + AI) 🚀

📍 Location: Mumbai

💼 Experience: 5+ Years

👨‍💻 Role: Java Full Stack Developer

Looking for an exciting career opportunity? We are hiring talented Java Full Stack Developers to join our growing team!

🔹 Required Skills:

• Java, Spring Boot & Microservices
• React.js
• Apache Kafka
• AWS Cloud Services
• AI technologies

📩 Interested candidates can share their updated resumes:

📧 Email:

revathi.r @vysystems. com

📞 Call / WhatsApp: 6 3 8 5 0 7 6 1 4 2

Junior PHP/Laravel Developer - Education ERP

Experience: 1.5 -3 Years

Employment Type: Full Time

Location : Remote

We are looking for a Junior PHP/Laravel Developer with hands -on experience in Core PHP ,Laravel ,and MySQL The candidate will work

on Education ERP/EdTech applications, developing new features, fixing

bugs ,handling databases,,and supporting existing applications.

Key Responsibilities

• Develop and maintain web applications using Core PHP and Laravel.
• Write and optimize My SQL/SQLqueries and perform database operations.

Looking for an Architect with strong experience in AI and Data Engineering, preferably with hands-on experience in Generative AI (GenAI). Candidates with experience in any cloud platform (AWS, Azure, or GCP) will be considered, 

Chief Engineer - Artificial Intelligence

AI Architecture | Production Engineering | LLM, RAG & Agentic AI

Primary objective: Build secure, scalable and reusable AI capabilities that move from experimentation to reliable production use across DocTutorials products and business functions.

Department

Technology & Product Engineering

Location

Hyderabad / Chennai

Reports to

Vice President - Technology

Experience

10+ years in software engineering, including 5+ years in AI/ML

Role Summary

The Chief Engineer - AI will define and lead AI engineering architecture, standards and production implementation. This is a senior, hands-on technical leadership role responsible for building reliable AI platforms and guiding AI engineers, data teams and application teams.

Key Responsibilities

1. AI Strategy and Architecture

·       Define the AI engineering strategy, architecture and technical roadmap.

·       Evaluate and select suitable models, frameworks, vector databases and AI platforms.

·       Make practical build-versus-buy and open-source-versus-commercial decisions.

·       Ensure AI solutions are modular, reusable, scalable, secure and cost-effective.

2. Production AI Engineering

·       Lead AI initiatives from use-case assessment and proof of concept through production deployment.

·       Build reusable AI services, APIs, pipelines and platform components for web, mobile and internal applications.

·       Establish development, testing, deployment, monitoring and production-support practices.

·       Resolve complex issues involving model quality, retrieval, performance, reliability and cost.

3. LLM, RAG and Agentic AI

·       Design LLM applications, enterprise RAG solutions and controlled AI-agent workflows.

·       Build document processing, chunking, embedding, indexing, retrieval and response pipelines.

·       Implement source traceability, human approval and clear permissions for sensitive use cases.

·       Improve response quality through prompt design, retrieval optimisation and evaluation.

4. AI Quality, Security and Responsible AI

·       Define evaluation standards for accuracy, relevance, groundedness, safety, latency and cost.

·       Introduce benchmark datasets and regression testing for prompts, models and retrieval pipelines.

·       Implement safeguards for hallucinations, unsupported responses, data leakage and unsafe actions.

·       Ensure role-based access, encryption, audit logging, secure secrets handling and approved data usage.

5. AI Platform and Integration

·       Create common AI capabilities and integration standards that can be reused across products and teams.

·       Integrate AI services with applications, databases and approved enterprise data sources.

·       Implement observability for model usage, quality, errors, response time and cost.

·       Reduce dependency on a single model provider, individual engineer or external vendor.

6. Technical Leadership and Team Development

·       Define AI engineering standards for architecture, coding, review, testing and documentation.

·       Remain hands-on through design reviews, critical code reviews, debugging and focused prototypes.

·       Mentor AI/ML engineers, data engineers and application teams; support hiring and capability building.

·       Work with Product and business teams to convert high-value problems into measurable AI solutions.

Required Skills and Experience

·       10+ years of software engineering experience, including 5+ years in practical AI/ML engineering.

·       Proven experience moving AI solutions from prototype to reliable production use.

·       Strong Python and production API development experience, preferably FastAPI.

·       Strong knowledge of LLMs, RAG, prompt engineering, embeddings and agentic AI.

·       Experience with vector databases such as pgvector, Qdrant, Milvus or Weaviate.

·       Experience with LangChain, LlamaIndex, Haystack or similar orchestration frameworks.

·       Knowledge of cloud architecture (preferably AWS), microservices, databases, queues and distributed systems.

·       Experience with Docker, Kubernetes, CI/CD, observability and production support.

·       Strong understanding of application security, data privacy and responsible-AI engineering.

·       Demonstrated technical leadership, mentoring and stakeholder-management capability.

Good-to-Have Experience

·       Healthcare, medical education, EdTech or digital-learning platforms.

·       Medical-content intelligence, knowledge graphs, ontologies, taxonomy or semantic search.

·       Clinical Case Library, personalised learning or recommendation systems.

·       Multi-modal AI involving text, audio, images or video.

·       Healthcare-data privacy, de-identification or standards such as SNOMED CT, ICD, HL7 or FHIR.

How Success Will Be Measured

·       Production adoption and measurable business or learner impact of AI capabilities.

·       Accuracy, groundedness, reliability, security and cost efficiency of AI solutions.

·       Reusable AI services delivered across products with reduced technical and vendor dependency.

·       Improved capability, engineering quality and ownership within the AI team.

We are looking for a hands-on AI engineering leader who can distinguish a valuable production capability from an attractive demo and build AI that is secure, scalable, measurable and maintainable.

Senior Trainer — AI/ML

Reports To: Associate Director / Head of L&D

Department: L&D-Corporate

Location: Gurgaon, Haryana & Bangalore

Job Summary

We are looking for a skilled and detail-oriented Trainer to design and deliver high-impact learning programs in AI/ML (including Generative AI), Digital Transformation, Technology, and Advanced Analytics.

The role emphasizes structured learning paths, engaging facilitation, and measurable outcomes aligned with company's domain-specific AI and analytics offerings. Key Responsibilities We seek an experienced AI Enablement professional to design and deliver high-impact learning programs in Generative AI, Agentic AI, AI Productivity, Data & Analytics, and Digital Transformation.

The role focuses on driving enterprise AI adoption through structured learning journeys, hands-on workshops, AI certifications, and business-aligned capability-building initiatives. The trainer will work closely with business leaders and SMEs to enable employees to leverage AI, automation, and intelligent agents.

Core Competencies

• Design and deliver instructor-led, virtual, and blended learning programs on Generative AI, Agentic AI, Large Language Models (LLMs), AI Engineering, Data Science, and enterprise AI platforms such as Microsoft Copilot, Copilot Studio, and Azure AI Foundry.

• Develop role-based curricula, learning journeys, certification pathways, and capability frameworks aligned to emerging AI technologies and business needs.

• Deliver hands-on workshops on AI applications, prompt engineering, AI agents, enterprise copilots, and workflow automation.

• Create practical learning experiences using tools such as Microsoft 365 Copilot, Copilot Studio, ChatGPT, Claude, Azure AI Services, and other enterprise AI platforms.

• Track learning effectiveness, adoption, business impact, and ROI using learner feedback, usage analytics, and performance metrics.

• Develop reusable prompts, agent templates, AI accelerators, and knowledge assets to support scalable learning initiatives.

• Leverage digital learning technologies, AI-powered learning platforms, and modern instructional methodologies to enhance learner engagement.

• Stay abreast of advancements in GenAI, Agentic AI, AI governance, Responsible AI, automation, and emerging technologies and continuously integrate them into learning programs.

Required Qualifications

• Master’s degree in Computer Science, Information Technology, Data Science, Artificial Intelligence, Analytics, or a related discipline

• 6–10 years of corporate training/L&D experience with strong focus on technology and analytics would be an added advantage.

• Hands-on expertise in Python and practical AI solution development, with experience in Generative AI tools, prompt engineering, and AI-powered productivity platforms.

• Working knowledge of LLM ecosystems, Retrieval-Augmented Generation (RAG), AI agents, automation frameworks, and enterprise AI applications.

• Experience with Microsoft Copilot, Copilot Studio, Power Platform, Azure AI Services, OpenAI technologies, or equivalent AI ecosystems.

• Strong understanding of cloud platforms such as Azure, AWS, or Google Cloud, with familiarity in AI and machine learning services.

Preferred Qualifications

• AI/ML & Generative AI concepts; model lifecycle and governance awareness.

• Instructional design, curriculum development, and assessment design.

• Strong facilitation, storytelling, and stakeholder management.

• Data-driven evaluation; dashboards and reporting for learning impact.

• Familiarity with company's platforms and decision-centric analytics approach.  

Thanks & Regards,

Arti Chopra

Bean HR Consulting-"Ahead Your Search"

https://beanhr.com

Locations:- Ghaziabad (Delhi-NCR) / Dehradun

Key Responsibilities

We seek an experienced AI Enablement professional to design and deliver high-impact learning programs in Generative AI, Agentic AI, AI Productivity, Data & Analytics, and Digital Transformation. The role focuses on driving enterprise AI adoption through structured learning journeys, hands-on workshops, AI certifications, and business-aligned capability-building initiatives. The trainer will work closely with business leaders and SMEs to enable employees to leverage AI, automation, and intelligent agents.

Core Competencies

• Design and deliver instructor-led, virtual, and blended learning programs on Generative AI, Agentic AI, Large Language Models (LLMs), AI Engineering, Data Science, and enterprise AI platforms such as Microsoft Copilot, Copilot Studio, and Azure AI Foundry.
• Develop role-based curricula, learning journeys, certification pathways, and capability frameworks aligned to emerging AI technologies and business needs.
• Deliver hands-on workshops on AI applications, prompt engineering, AI agents, enterprise copilots, and workflow automation.
• Create practical learning experiences using tools such as Microsoft 365 Copilot, Copilot Studio, ChatGPT, Claude, Azure AI Services, and other enterprise AI platforms.
• Track learning effectiveness, adoption, business impact, and ROI using learner feedback, usage analytics, and performance metrics.
• Develop reusable prompts, agent templates, AI accelerators, and knowledge assets to support scalable learning initiatives. Sensitivity: Public evalueserve.com
• Leverage digital learning technologies, AI-powered learning platforms, and modern instructional methodologies to enhance learner engagement.
• Stay abreast of advancements in GenAI, Agentic AI, AI governance, Responsible AI, automation, and emerging technologies and continuously integrate them into learning programs.

Required Qualifications

• Master’s degree in Computer Science, Information Technology, Data Science, Artificial Intelligence, Analytics, or a related discipline
• 6–10 years of corporate training/L&D experience with strong focus on technology and analytics would be an added advantage.
• Hands-on expertise in Python and practical AI solution development, with experience in Generative AI tools, prompt engineering, and AI-powered productivity platforms.
• Working knowledge of LLM ecosystems, Retrieval-Augmented Generation (RAG), AI agents, automation frameworks, and enterprise AI applications.
• Experience with Microsoft Copilot, Copilot Studio, Power Platform, Azure AI Services, OpenAI technologies, or equivalent AI ecosystems.
• Strong understanding of cloud platforms such as Azure, AWS, or Google Cloud, with familiarity in AI and machine learning services. Preferred Qualifications
• AI/ML & Generative AI concepts; model lifecycle and governance awareness.
• Instructional design, curriculum development, and assessment design.
• Strong facilitation, storytelling, and stakeholder management.
• Data-driven evaluation; dashboards and reporting for learning impact.

Role Overview: Take full ownership of infrastructure architecture, scaling, and uptime. Establish the technical roadmap, shape and formalize the SRE function, and coach engineers. Design, deploy, and run AI-scale infrastructure that enables real-time healthcare workflows.

Serve as a Founding Member, owning end-to-end infrastructure capabilities and introducing AI-first DevOps, SRE, and MLOps best practices, with direct collaboration alongside the Founder, Co-Founder, and Head of Engineering.

Key Responsibilities:

Architecture & Platform

• Design scalable, secure, cost-efficient AWS/GCP architectures for AI and healthcare workloads
• Lead IaC standards and reusable modules org-wide; own GitOps practices
• Architect optimized Kubernetes (EKS/GKE) for HA, scale, and GPU workload orchestration

Reliability Engineering

• Define and drive reliability targets (SLOs/SLIs); establish SRE practice
• Lead incident management, RCA, and blameless post-mortems for critical systems
• Partner on infrastructure hardening and compliance (SOC 2, HIPAA)

AI-First Engineering

• Lead AI/ML inference and GPU infrastructure scaling in production
• Evaluate and introduce AI tooling, platforms, and automation best practices
• Contribute to LLM deployment pipelines and AI systems reliability

Leadership & SDLC

• Mentor L1/L2 engineers; influence cross-team infrastructure decisions
• Drive DevSecOps maturity across the SDLC (policy-as-code, SBOM, supply-chain security)
• Evaluate and introduce new tooling and platforms

Key Requirements:

• 4–8 years infrastructure/platform/DevOps/SRE
• Deep expertise in AWS & GCP large-scale production systems
• Advanced Kubernetes (cluster design, multi-tenant ops, resource quotas)
• AI/ML inference or GPU infrastructure scaling (production track record)
• Strong Terraform / equiv. and GitOps practices
• Python, Go, or Bash scripting and automation
• Track record in scale, reliability, and cost efficiency
• Lead incident response and on-call practices

Nice-to-Have

• LLM Gateway architecture and optimization
• Zero-trust networking and advanced security/compliance (SOC 2, HIPAA)
• DevSecOps maturity: SBOM, supply-chain security, policy-as-code
• Open-source contributions or platform-team leadership

Why This Role?

• Build infrastructure and products powering real-world healthcare AI
• Work with AI-native engineering teams using cutting-edge tools (Claude Code, Cursor, Copilot)
• Mission-driven impact — improve patient outcomes and save thousands of staff hours
• High ownership, rapid learning, and significant career upside
• Global collaboration across India and the US
• Seed-stage growth — scale from Seed to Series A alongside the team
• Founding Member role and own the entire infrastructure capabilities, including bringing best AI-first practices in DevOps, SRE and MLOps; direct access to work with the Founder, Co-Founder and Head of Engineering

Why this role exists 

Most systems work at a low scale. 

Very few survive real production load, complex workflows, and enterprise edge cases. 

We are building a platform that must: 

1. Scale from 500K → 20M+ interactions/month 
2. Handle complex insurance workflows reliably 
3. Become easier to deploy as it grows, not harder 
4.  
5. This role exists to build the backend foundation that makes this possible. 

What you’ll do 

You will not just write services. 

You will design and own core platform systems. 

1. Scale the platform without breaking architecture 

1. Scale from 50K → 4M+ interactions/month 
2. Ensure: 
3. High availability 
4. Low latency 
5. Fault tolerance 
6. Avoid large rewrites — build systems that evolve cleanly 

2. Build the workflow automation (WA) engine 

1. Design a flexible system with: 
2. States 
3. Stages 
4. Cohorts 
5. Dynamic workflows 
6. Ensure workflows: 
7. Handle edge cases reliably 
8. Can be configured easily 
9. Move from: 
10. Hardcoded flows → configurable execution engine 

3. Build the insurance-specific data layer 

1. Design data models for: 
2. Policy states 
3. Claim workflows 
4. Consent tracking 
5. Ensure the system works across: 
6. Multiple insurers 
7. Multiple use cases 
8. Build a platform-first data layer, not use-case-specific hacks 

4. Make deployment and setup simple 

1. Ensure workflows and data models are: 
2. Easy to configure 
3. Easy to launch 
4. Reduce friction for: 
5. Product teams 
6. Deployment teams 

5. Create a compounding data advantage 

1. Build a data layer that: 
2. Improves with every deployment 
3. Captures structured signals 
4. Ensure data becomes a long-term edge, not just storage 

6. Own production reliability 

1. Participate in on-call rotation across 3 engineers 
2. Ensure: 
3. Incidents are handled quickly 
4. Root causes are fixed permanently 
5. Build systems where reliability is shared, not individual 

What success looks like 

1. Platform scales to 2M+ interactions/month smoothly 
2. Workflow engine supports complex, dynamic use cases 
3. Data layer enables fast deployment across accounts 
4. Edge cases are handled without constant firefighting 
5. System becomes easier to use as it grows 
6. Production issues are rare and predictable 

Who you are 

1. You have built: 
2. Scalable systems 
3. Distributed services 
4. You think in: 
5. Systems 
6. Data models 
7. Trade-offs 
8. You are comfortable owning: 
9. Architecture 
10. Production systems 

What will make you stand out 

1. Experience building: 
2. Workflow engines 
3. State machines 
4. Data-heavy platforms 
5. Strong understanding of: 
6. System design 
7. Distributed systems 
8. Failure handling 
9. Experience working in: 
10. High-scale production environments 

Why join 

1. You will build the core backend of an AI platform 
2. Your work directly impacts: 
3. Scale 
4. Reliability 
5. Product capability 
6. You will design systems that move from: 
7. Use-case specific → platform-level infrastructure 

What this role is not 

1. Not just API development 
2. Not limited to feature-level work 
3. Not disconnected from production realities 

What this role is 

1. A system architect 
2. A builder of scalable platforms 
3. A driver of long-term technical advantage 

One question to self-evaluate 

Can you design backend systems that scale, handle edge cases, and become easier to use as they grow? 

Job Title: Java SDET / Automation Test

Experience: 5+ Years

Location: Hyderabad

Work Mode: 4 Days WFO

Interview Process:

• L1: Case Study – GitHub Repository
• L2: Face-to-Face – Hyderabad

Job Summary

We are looking for an experienced Java SDET / Automation Test Lead with strong expertise in Java, Selenium, automation testing, and AI-powered testing tools. The candidate will be responsible for leading automation testing activities, developing robust test frameworks, ensuring product quality, and improving testing efficiency using AI tools.

Mandatory Skills

• Java
• Selenium WebDriver
• Automation Testing / SDET
• Test Automation Frameworks
• Test Planning & Test Case Development
• AI Tools for Development & Test Automation
• End-to-End Testing
• Test Data Creation
• Defect Tracking

Preferred Skills

• AI Testing Frameworks
• API Testing – Postman / SoapUI
• Performance Testing
• CI/CD
• Agile/Scrum
• Database Testing & SQL

Roles & Responsibilities

• Lead software testing activities and ensure high-quality deliverables.
• Design, develop, and execute automated test scripts using Java and Selenium.
• Develop and maintain test plans, test cases, and test data.
• Identify, document, and track defects.
• Mentor and guide junior testers.
• Collaborate with development teams to improve testability and automation strategies.
• Use AI tools to improve testing and automation efficiency.
• Participate in code reviews and contribute to testing best practices.
• Perform end-to-end testing and ensure application quality.
• Report testing progress and results to stakeholders.

📩 Interested candidates can share their updated resumes:

Email: pavithra.e @vysystems. com

Contact: 8 9 2 5 8 0 2 4 5 7

We're building the AI operating system for the $600B global managed IT market.

Managed service providers (MSPs) run IT for lots of small and mid-sized businesses. Their technicians spend most of the day on repetitive tickets — setting up new joiners, sharing folders, fixing sign-in issues. Our first product is an AI service desk. It learns how each MSP works, turns a ticket into a plan of exact steps, and runs only what a technician approves.

Our vision is to build additional products for other parts of the MSP's business (such as voice AI, business operations and analytics), turning this into the one AI operating layer for the MSP business.

We've just raised a $4.4M pre-seed from Seedcamp, Futurepresent and Entree Capital. Our founders previously built upGrad ($2B) and Kapiva ($250M), and come from Bain Capital, Parthenon, and Morgan Stanley. Our co-founders both studied CS at IIT Delhi.

We're building a small team with very high talent density in Mumbai — people from IIT Bombay, Yale, Rippling and more.

The role:

We're hiring our first Product Designer — someone who will shape how the product looks, feels, and works from the ground up.

The hardest design problem we have is trust. A technician needs to feel comfortable letting AI make changes in a customer's Microsoft 365 or Google Workspace. So every screen needs to make it very clear what the AI knows, what it plans to do, and what it changed — and still be fast enough that a busy service desk actually uses it.

You'll work directly with the co-founder who leads product and our engineers, and own design end to end — from customer calls to shipped product.

What you'll do:

• Own the product experience end to end. Take problems from a first customer conversation to rough sketches, prototypes, and polished UI that ships — then keep improving it once it's live.
• Design how people and AI work together. Decide how the product explains what it knows, asks for approval, shows its progress, and owns up when something goes wrong. Make it easy for a technician to say yes with confidence.
• Make complex work feel simple. IT work is detailed and technical. You'll turn it into clear, fast experiences that busy teams can use without training.
• Stay close to customers. Join customer calls, watch technicians at work, test ideas with them every week, and bring what you learn straight into the product.
• Prototype fast, ideally in code. Use AI and design tools (Claude, Figma and others) to build working prototypes, so we learn from real use rather than static mockups.
• Design everywhere the product shows up — the app, integrations with tools technicians already use, operational dashboards and more.
• Build a lean design system. Give our engineers the building blocks to ship consistent UI without waiting on you.
• Set the bar for design. As our first designer, you'll shape how design is done here — the standard of quality, how we work, and who we hire next.

A few problems you might pick up in your first months: a single approval to set up 50 new joiners, with a clear "48 done, 2 need attention — and why"; a way for teams to see what the AI has learnt about each client, where it came from, and how to undo it; and a simple view that tells an owner the AI is working.

What we're looking for:

• Great product design work you've actually shipped. Consumer or B2B doesn't matter — we care much more about how you think than where you've worked.
• Strong craft and taste. Simple, clean and fast over flashy — think Linear, not a design studio website.
• Comfort going deep on a complex subject. You'll need to learn how things like Microsoft 365 groups and licences work, and enjoy doing it.
• Speed. You prototype in code or with AI tools and get ideas in front of users quickly.
• You use AI every day. You have opinions on what makes AI products feel trustworthy — and what makes them feel risky.
• High ownership and clear writing. You can take a messy problem all the way to something shipped, and explain your thinking simply along the way.

Nice to have:

• You've designed AI or agent products before.
• Early-stage startup or founder experience.
• You can write front-end code (React / Tailwind).

Probably not the right fit if

• Most of your work is brand, marketing, or research.
• You need a detailed spec and a design manager to do your best work.

Why join us?

• Real ownership. We're very early, so you'll shape how design works here — not inherit someone else's system.
• A hard, new problem. AI that takes real actions on real systems is still being figured out. You'll help define what good looks like.
• Fast impact. You'll work directly with the founders and see your work in customers' hands within weeks.

AI Engineer

Focus: Agentic AI, AI Shopping Assistants & Virtual Try-On

Role Summary :

We are looking for a Full-Stack AI Engineer to build, deploy, and operate production-grade AI applications, including agentic shopping assistants and multimodal AI experiences. The role requires strong hands-on expertise in Python, TypeScript, LLM-based applications, real-time streaming, evaluation, and cloud infrastructure.

The ideal candidate can independently deliver end-to-end features across backend agent runtimes and frontend interfaces, with a strong focus on reliability, latency, cost optimisation, and production performance.

Key Responsibilities :

• AI Agent Development: Build and maintain Python-based agent runtimes using LLMs, tool calling, structured outputs, retrieval-augmented generation (RAG), multi-turn state, and human escalation workflows.
• Full-Stack Engineering: Develop asynchronous Python APIs and TypeScript web components, implementing server-sent events (SSE), streaming interfaces, interactive product cards, and resilient client-side error handling.
• LLM Evaluation: Build evaluation datasets and automated test harnesses using deterministic and model-based graders, regression gates, ablation studies, and pass@k/pass^k metrics.
• Performance & Cost Optimisation: Improve response latency, time to first token, token consumption, caching efficiency, context management, and cost per conversation.
• Production Operations: Implement distributed tracing, structured logging, LLM observability, monitoring, incident resolution, feature flags, controlled rollouts, and rollback mechanisms.
• Cloud & DevOps: Deploy containerised services, manage CI/CD pipelines, infrastructure as code, and production workloads on cloud platforms.
• E-commerce AI Integration: Integrate product search, catalogue data, product details, grounded recommendations, and commerce-related event tracking into AI-powered shopping experiences.
• Virtual Try-On & Multimodal AI: Contribute to image-based generative AI applications, including embeddable frontend widgets and scalable backend services.
• Internationalisation & Scalability: Support multilingual experiences, brand-specific configurations, localisation, currency handling, and backward-compatible integrations.
• Cross-Functional Collaboration: Work with product, business, and engineering stakeholders to troubleshoot quality issues and deliver measurable improvements to customer experience and business outcomes.

Essential Skills & Experience :

• Strong hands-on experience with Python and TypeScript.
• Production experience building LLM-powered applications using tool/function calling, structured outputs, streaming, retries, context management, and RAG.
• Strong understanding of asynchronous Python, REST APIs, SSE, and event-driven communication.
• Practical experience designing LLM evaluation frameworks, test datasets, automated graders, regression testing, and evaluation metrics.
• Experience deploying and operating cloud-based applications, containerised services, CI/CD pipelines, and infrastructure as code.
• Familiarity with production observability, distributed tracing, structured logging, performance monitoring, and incident management.
• Experience with caching, latency optimisation, token and inference cost management, feature flags, and safe deployment strategies.
• Strong software engineering fundamentals, debugging skills, and end-to-end ownership of production features.

Preferred Skills :

• Experience with agent frameworks such as Google ADK, LangGraph, or Claude Agent SDK.
• Hands-on exposure to Google Cloud Platform, Vertex AI, Gemini, FastAPI, and Cloud Run.
• Experience with frontend frameworks and tools such as Lit, Next.js, esbuild, and Vitest.
• Familiarity with PostgreSQL, BigQuery, OpenTelemetry, Opik, and LLM tracing platforms.
• Knowledge of MCP servers, sub-agents, agent-to-agent integrations, and retrieval systems.
• Experience with e-commerce search, multimodal AI, image generation, virtual try-on, and third-party web embeds.
• Understanding of prompt-injection mitigation, multilingual applications, and inference performance optimisation.
• Effective use of AI coding assistants and developer productivity tools.

Role Expectations :

• Deliver production-ready features across both backend AI services and frontend applications.
• Demonstrate evaluation evidence, observability, and safe rollout practices for AI-driven changes.
• Balance response quality, reliability, latency, infrastructure costs, and user experience.
• Work effectively within existing systems, maintaining backward compatibility and planning migrations and rollbacks.
• Take ownership of troubleshooting, continuous improvement, and production reliability.

Strong AI Engineer / Machine Learning Engineer profiles.

2

Mandatory (Experience 1) – Must have minimum 3+ years of hands-on experience in Data Science, Machine Learning, Applied AI, NLP, Deep Learning, or Generative AI solutions.

3

Mandatory (Experience 2) – Must have strong hands-on experience in Python programming, SQL, data analysis, feature engineering, model development, and production-grade ML applications.

4

Mandatory (Experience 3) – Must have experience working with Machine Learning and Deep Learning frameworks such as PyTorch, TensorFlow, Keras, Scikit-learn, or equivalent.

5

Mandatory (Experience 4) – Must have hands-on experience working on NLP, embeddings, semantic search, text classification, document understanding, recommendation systems, or similar AI/ML use cases.

6

Mandatory (Experience 5) – Must have experience working with Large Language Models (LLMs) such as GPT, Llama, Mistral, Claude, Gemini, Phi, or similar foundation models.

7

Mandatory (Experience 6) – Must have hands-on experience building or implementing RAG (Retrieval Augmented Generation) systems, vector search, knowledge retrieval, embeddings, chunking, indexing, or semantic retrieval solutions.

8

Mandatory (Experience 7) – Must have experience working with Git, CI/CD practices, production environments, and scalable AI/ML systems.

Mandatory ( Pedigree) - B.TECH / M.TECH from Tier 1 Colleges (IIT's, NIT's, BITS) are Considered.

Strong Data Scientist / AI Engineer / Generative AI Engineer profile.

2

Mandatory (Experience 1) - Must have 3+ years of hands-on experience in Data Science, Artificial Intelligence, Machine Learning, Deep Learning, NLP, or Generative AI application development.

3

Mandatory (Experience 2) - Must have strong hands-on experience in Python programming, backend development, API development, and production-grade application support.

4

Mandatory (Experience 3) - Must have experience working with Machine Learning and Deep Learning frameworks such as PyTorch, TensorFlow, Keras, or Scikit-learn.

5

Mandatory (Experience 4) - Must have hands-on experience in NLP use cases such as text classification, sentiment analysis, entity recognition (NER), semantic search, embeddings, or document understanding.

6

Mandatory (Experience 5) - Must have experience working with Large Language Models (LLMs) such as GPT, LLaMA, Mistral, Phi, Claude, Gemini, or similar models.

7

Mandatory (Experience 6) - Must have hands-on experience building or implementing Retrieval Augmented Generation (RAG) solutions, vector search, semantic search, or knowledge-based AI applications.

8

Mandatory (Experience 7) - Must have experience with Prompt Engineering and Generative AI frameworks such as LangChain, LangGraph, AI Agents, Azure OpenAI, or similar technologies.

9

Mandatory (Experience 8) - Must have experience developing, consuming, or integrating APIs using Python frameworks such as FastAPI, Flask, or similar technologies.

Mandatory (Education) - B.TECH / M.TECH from Tier 1 Colleges (IIT, NIT, BITS, IIIT, DTU, NSUT) are considered.

Strong Lead AI Engineer Profile with agentic systems architecture expertise

2

Mandatory (Experience 1): Must have 6+ years of software or ML engineering, with at least recent 2+ years building and shipping production LLM or agentic AI systems

3

Mandatory (Tech skill 1): Must have hands-on proficiency with at least two agentic frameworks (LangGraph, LangChain, AutoGen, CrewAI), with experience debugging framework internals

4

Mandatory (Tech skill 2): Must have direct SDK experience with Anthropic Claude API (tool use, streaming), OpenAI Assistants API, or Vertex AI Agent Builder

5

Mandatory (Tech skill 3): Must have Python mastery — production-quality code, type annotations, unit and integration tests, packaging, and performance profiling

6

Mandatory (Tech skill 4): Must have RAG pipeline depth — embedding model selection, vector stores (Pinecone, Weaviate, pgvector), hybrid retrieval, RAGAS or custom evaluation harnesses

7

Mandatory (Tech skill 5): Must have cloud deployment experience with AWS, Azure, or GCP; Docker, Kubernetes, IaC basics (Terraform or CDK), and CI/CD pipelines

8

Mandatory (Tech skill 6): Must have agent observability experience — LangSmith, Helicone, or equivalent — with ability to diagnose latency, cost, and quality issues in production traces

9

Mandatory (Tech skill 8) : Must have owned full sub-system designs — agent topology, data flows, API contracts, failure handling — for a bounded scope, and built multi-agent graphs, tool orchestration, retrieval, and memory systems.

10

Mandatory (Tech skill 7): Must have track record of shipping 2+ agentic or ML systems to production — not just proof-of-concepts — with documented performance benchmarks

11

Mandatory (Communication): Must be able to write crisp component specifications and communicate architectural trade-offs to both engineers and non-technical stakeholders

12

Mandatory (Note 1) : Role is Hybrid, WFH flexibility as well upto 6 days a month

We are looking for a Senior Full Stack Engineer to join our lean, high-impact engineering team. This is a key founding-team role where you will work closely with the CTO and help build the engineering foundation of the company.

The ideal candidate is a backend-strong full-stack engineer with solid Python and React experience, a strong understanding of AI/LLMs, and the ability to independently take ownership of projects from idea to production.

What You'll Do:

• Build and scale applications across the backend and frontend
• Develop backend services and APIs using Python
• Build and maintain frontend applications using React
• Design and implement AI/LLM-powered applications and features
• Work with AI services and integrate them into real-world applications
• Contribute to system design and architecture
• Work with cloud infrastructure and services
• Take ownership of features and initiatives from ideation to production
• Identify problems and proactively drive solutions without requiring constant direction
• Work closely with the CTO and founding team to shape engineering practices and future systems
• Communicate technical concepts clearly to technical and non-technical stakeholders

What We're Looking For:

• 3–6 years of software engineering experience
• Strong experience with Python
• Good hands-on experience with React
• Strong backend development experience with full-stack exposure
• Practical understanding of AI, LLMs and AI services
• Experience building at least one meaningful AI project beyond basic API/chatbot integrations
• Experience taking an AI/ML application or feature into production is preferred
• Exposure to cloud platforms
• Good understanding of system design and software architecture
• Strong problem-solving and ownership mindset
• Excellent communication skills and ability to explain complex technical concepts in simple language
• Genuine hands-on experience with the technologies mentioned on the resume

What Makes This Role Different:

This is not a typical execution-focused engineering role. We are building a lean "A-team" of experienced engineers who will eventually help shape the team and take on senior/leadership responsibilities.

We're looking for someone who:

• Takes initiative rather than waiting for tasks
• Can work independently in an early-stage environment
• Is comfortable exploring and building with AI
• Can go deep into the work they've done and explain the technical decisions behind it
• Wants significant ownership and influence over the product and engineering direction

Location & Compensation

• Work Mode: Remote initially
• Future Location: Expected relocation to Bangalore in approximately 1 year
• Working Hours: Regular IST hours
• Travel: Potential opportunities to travel to Germany

Interview Process:

3 Rounds

1. Technical & Project Deep Dive – Conversational discussion around past projects, AI experience and technical depth
2. System Design & Technical Round – Deeper technical and architecture discussion
3. Founder Round – Communication, culture fit, ownership and initiative

We’re Hiring | Technology Lead – Java & AWS

Locations: Kochi | Trivandrum | Bangalore

Experience: 15–18 Years

Key Skills: Java, AWS, AI/ML

What We’re Looking For

Strong hands-on expertise in Java and enterprise application development.

Solid experience with AWS and cloud-based architectures.

Practical experience implementing AI/ML solutions.

Expertise in solution architecture, system integration, and scalable application design.

Proven ability to lead technical initiatives while remaining actively involved in coding, design, and troubleshooting.

Experience delivering end-to-end enterprise solutions.

What you’ll actually do

You’ll own the execution side of paid campaigns for our client accounts. This isn’t a coordinator role. You’ll be inside ad accounts every single day.

Campaign Execution

• Build, launch, and manage Meta and Google Ads campaigns end-to-end (sales, lead gen, traffic, conversions)
• Set up campaign structures, ad sets, audiences, placements, and creative rotations
• Upload creatives, write ad copy variations, and set up A/B tests
• Manage budgets, pacing, and bid strategies across accounts

Optimization and Analysis

• Monitor account performance daily — CTR, CPM, CPC, CPA, ROAS, frequency
• Identify winning and losing ad sets, scale or kill based on data
• Diagnose drops in performance (creative fatigue, audience saturation, attribution issues) and propose fixes
• Pull weekly performance reports and flag what’s working and what isn’t

Creative and Landing Page Collaboration

• Brief the creative team (or external designers) on ad creative needs based on what’s working
• Work with the founder to test landing page variants and recommend CRO experiments
• Stay on top of creative trends in D2C, especially for premium and lifestyle brands

AI-First Workflow

You will use AI tools every single day. This isn’t optional and it isn’t a buzzword — it’s how we work

• Use Claude, ChatGPT, or similar LLMs for ad copy generation, audience research, competitor analysis, and brief writing
• Use AI image and video tools (Midjourney, Runway, Sora, Google Veo, ElevenLabs, etc.) for creative ideation and rapid creative variants
• Build prompt workflows for repetitive tasks — reporting, audience research, copy variations
• Stay current on new AI tools as they launch and bring ideas to the team
• If your instinct is to do something manually that AI could do in 1/10th the time, you’re working wrong here

Client Communication

This is roughly 30–40% of the role. You’ll be client-facing from week one

• Run weekly performance review calls with clients — present numbers, explain what’s happening, recommend next steps
• Respond to client messages on WhatsApp/email within working hours, professionally and with data
• Write structured weekly performance reports clients can read in 5 minutes
• Manage client expectations on timelines, results, and creative deliverables
• Flag risks early — a campaign trending down, a creative pipeline running thin, a tracking issue — before clients have to ask

What we’re looking for

Must have

• 1–2 years of hands-on experience running Meta Ads and Google Ads (Search, Performance Max, Shopping)
• You’ve personally managed monthly spends of at least ₹2–5 lakhs across accounts
• Strong grasp of Meta Ads Manager — campaign objectives, Advantage+, custom audiences, lookalikes, pixel/CAPI setup
• Comfortable with Google Ads — keyword research, Search campaigns, conversion tracking, PMax basics
• Active daily user of AI tools (Claude, ChatGPT, Midjourney, or similar). You can show us prompts you’ve actually written and workflows you’ve built
• Confident on client calls — you can present numbers, hold your ground, and explain things clearly without jargon
• Solid Excel/Google Sheets skills — pivot tables, basic formulas, building performance dashboards
• Analytical mindset — you can look at a table of numbers and tell a story
• Clear written communication in English — your WhatsApp messages and emails will go directly to founders of premium brands

Nice to have

• Experience with D2C or ecommerce brands (Shopify, WooCommerce)
• Familiarity with GA4, Meta Pixel events, conversion API setup
• Exposure to creative testing frameworks and ad copy writing
• Worked at an agency before (you understand client cadence)
• 
  

Job Description – Squad Lead

Location: Kochi, Kerala

Experience: 10+ Years

Role: Squad Lead

Notice Period: Immediate to 30 Days

About the Role

We are looking for an experienced and technically strong Squad Lead to join our engineering team in Kochi. The ideal candidate will have 10+ years of software development experience, with strong expertise in Java, Spring Boot, Microservices, Angular, and AI technologies.

The Squad Lead will be responsible for leading a cross-functional engineering squad, driving technical excellence, mentoring team members, and ensuring the successful delivery of scalable and high-quality software solutions.

Key Responsibilities

• Lead and manage a software engineering squad, ensuring successful delivery of projects and product initiatives.
• Provide strong technical leadership and hands-on guidance to the development team.
• Design and develop scalable, secure, and high-performance applications using Java, Spring Boot, and Microservices.
• Drive the adoption and integration of AI/GenAI technologies into products and engineering solutions.
• Collaborate with frontend teams and contribute to applications developed using Angular.
• Define technical approaches, architecture, coding standards, and best practices.
• Conduct code reviews and ensure adherence to engineering and quality standards.
• Mentor and coach developers, helping them grow technically and professionally.
• Work closely with Product Managers, Business Analysts, Architects, QA, DevOps, and other stakeholders.
• Break down complex requirements into actionable technical tasks and sprint deliverables.
• Participate in solution design, estimation, planning, and technical discussions.
• Identify technical risks and proactively drive their resolution.
• Ensure timely delivery while maintaining high standards of code quality, performance, security, and maintainability.
• Promote Agile/Scrum practices and foster a culture of collaboration, ownership, and continuous improvement.

Required Skills & Experience

• 10+ years of experience in software development, with significant experience in technical leadership.
• Strong hands-on experience with Java and Spring Boot.
• Strong understanding and practical experience with Microservices architecture.
• Experience developing and integrating RESTful APIs.
• Good experience with Angular and modern frontend development practices.
• Exposure to AI/ML, Generative AI, or AI-powered application development.
• Proven experience in leading software engineering squads/teams.
• Strong understanding of software architecture, design patterns, scalability, and performance.
• Experience working in Agile/Scrum development environments.
• Strong problem-solving, analytical, communication, and stakeholder-management skills.

Good to Have

• Experience with AWS and cloud-native application development.
• Knowledge of AWS services such as EC2, S3, Lambda, ECS/EKS, RDS, API Gateway, and CloudWatch.
• Experience with CI/CD, Docker, Kubernetes, and DevOps practices.
• Exposure to event-driven architectures and messaging platforms such as Kafka.
• Experience with cloud security, observability, and application performance monitoring.

Leadership Competencies

The successful candidate should demonstrate:

• Proven experience leading and mentoring engineering teams.
• Strong ownership and accountability for delivery.
• Ability to make sound technical decisions and influence stakeholders.
• Excellent communication and collaboration skills.
• Ability to manage priorities and deliver under tight timelines.
• A continuous-learning mindset with an interest in emerging technologies, particularly AI and cloud.

Education

• Bachelor's or Master's degree in Computer Science, Engineering, Information Technology, or a related discipline.

ou will work closely with AI engineers, product teams, and domain experts to build intelligent document processing and knowledge automation solutions. Responsibilities include:

• Develop AI-powered document ingestion and processing pipelines.
• Build knowledge extraction engines using NLP, Machine Learning, and Generative AI.
• Develop document-to-knowledge compilers that transform PDFs, Word documents, policies, regulations, and manuals into structured knowledge.
• Build AI agents and Agentic AI workflows for enterprise automation.
• Develop rule extraction and rule generation frameworks from business documents.
• Create semantic search and enterprise knowledge retrieval solutions.
• Develop backend APIs and AI services using Python.
• Design and optimize document processing pipelines for scalability and performance.
• Build and maintain MySQL databases for knowledge repositories and AI applications.
• Integrate LLMs from providers such as OpenAI, Azure OpenAI, Gemini, Claude, and open-source ecosystems.
• Collaborate with cross-functional teams to design scalable AI architectures.
• Participate in code reviews and follow software engineering best practices.
• Continuously evaluate and adopt emerging AI and GenAI technologies.

REQUIRED SKILLS — PROGRAMMING & DEVELOPMENT

• Strong proficiency in Python and a solid understanding of Object-Oriented Programming (OOP).
• Experience building REST APIs and backend services.
• Experience working with JSON, XML, and structured data formats.
• Knowledge of software design patterns and scalable architecture.
• Strong debugging, analytical, and problem-solving skills.

ARTIFICIAL INTELLIGENCE & MACHINE LEARNING

• Strong understanding of Machine Learning concepts and algorithms.
• Experience with Natural Language Processing (NLP) and Generative AI solutions.
• Hands-on experience with Large Language Models (LLMs).
• Understanding of prompt engineering techniques.
• Knowledge of Agentic AI concepts and AI agent architectures.
• Experience developing AI-powered applications and workflows.

TECHNOLOGY STACK

AI & GenAI: Python · OpenAI · Azure OpenAI · Hugging Face · Agentic AI Frameworks · LLMs · NLP · Machine Learning

Knowledge Systems: ChromaDB · Pinecone · FAISS · Vector Databases · Semantic Search

Document Processing: Docling · OCR · PDF Processing · Apache Tika · Document Intelligence

Backend: Python · FastAPI · Flask · REST APIs

Database: MySQL

Tools & Technologies: Git · Docker · JSON · CI/CD · Azure / AWS / GCP

Amura’s Vision

We believe that the most under-appreciated route to releasing untapped human potential is to build a healthier body, and through which a better brain. This allows us to do more of everything that is important to each one of us.

Billions of healthier brains, sitting in healthier bodies, can take up more complex problems that defy solutions today, including many existential threats, and solve them in just a few decades. Billions of healthier brains will make the world richer beyond what we can imagine today. The surplus wealth, combined with better human capabilities, will lead us to a new renaissance, giving us a richer and more beautiful culture. These healthier brains will be equipped with deeper intellect, be less acrimonious, more magnanimous, and have a kinder outlook on the world, resulting in a world that is better than any previous time.

We find this vision of the future exhilarating. Our hopes and dreams are to create this future as quickly as possible and ensure that it is widely distributed and optimized to maximize all forms of human excellence.

Role Overview

We are looking for a Senior Software Engineer - Frontend with strong ReactJS expertise and an AI-first mindset to build scalable, high-performance and AI-powered experiences for Amura’s digital health platform.

You will work closely with Product, Design, Backend and AI teams to build modern, usercentric products in a fast-moving environment.

Key Responsibilities

•  Build scalable, responsive and high-performance web applications using ReactJS, JavaScript and TypeScript.

•  Develop reusable frontend components and translate Figma designs into production-ready experiences.

•  Integrate REST APIs and AI/LLM-powered capabilities into frontend applications.

•  Build frontend experiences for AI-native use cases such as conversational workflows, intelligent recommendations, search and automation.

•  Use AI-assisted development tools such as Cursor, Claude Code, GitHub Copilot, Windsurf or similar for coding, debugging, testing and documentation.

•  Evaluate AI-generated code and ensure it meets standards for quality, security, performance and maintainability.

•  Optimize frontend performance, Core Web Vitals, rendering and bundle size.

•  Write tests, participate in code reviews and contribute to frontend architecture and engineering best practices. .

What We’re Looking For Required Skills:

•  4 to 6 years of professional frontend development experience. •  Strong proficiency in ReactJS, JavaScript and TypeScript.

•  Strong understanding of React Hooks, functional components, component architecture and state management.

•  Experience with REST APIs, responsive design and frontend performance optimization.

•  Experience translating Figma designs into production-ready UI. •  Hands-on experience with AI-assisted development tools. •  Familiarity with integrating LLM/AI APIs into applications.

•  Strong problem-solving and analytical skills. Engineering & AI Expectations

•  Strong understanding of browser rendering, Core Web Vitals and accessibility.

•  Experience with lazy loading, code splitting, caching and bundle optimization.

•  Experience with Next.js and frontend testing frameworks such as Jest, React Testing Library or Playwright is a plus.

•  Experience building AI-powered or AI-native applications is a plus. •  Familiarity with LLMs, RAG, embeddings, tool calling or AI agents is an advantage.

•  Strong ownership, product thinking and ability to work in a fast-paced 0→1 environment.

•  Curious about emerging AI technologies and able to use AI as a development multiplier while maintaining strong engineering judgment.

Here are answers to some questions you may have

Where is your office?

Chennai (Velachery) Work Model Work from Office – because great stories are built in person!

Do you have an online presence?

https://amura.ai (we are @AmuraHealth on all social media)

For better insights: https://drive.google.com/file/d/11UHgXqYc7XSJ3IAdFyEm-EurgOzqsmzA/view?usp=sharing 

Job Description

Who are we?

Interestingly, in our own corner of the world, a hardworking team bent on hyper-excellence has quietly built a new way of medicine, a platform built on science, story, and soul.

Think of Amura as a "hospital on the cloud." We help people achieve the best standard of health they possibly can, taking full responsibility for their journey. We're a team of curious, ambitious individuals across all fields of work. Here, Doctors work alongside health coaches, designers, engineers, writers, and even filmmakers.

A cloud can reach anywhere and so can we. Our patients are from all over the world, and we are changing lives globally from your new home in Chennai. Over the last 8 years we have helped tens of thousands of people live better lives across 45 countries. 

Role Overview

We are looking for a hands-on Senior Software Engineer - Mobile to build and scale high-quality mobile experiences at Amura Health.

You will work primarily with React Native across both Android and iOS, partnering closely with Product, Design and Backend teams to build reliable, performant and user-friendly applications.

This role is ideal for an engineer who takes ownership, solves problems independently and uses AI-assisted development to build, test, debug and ship software faster without compromising engineering quality. 

What you'll do :

● Build, enhance and maintain React Native applications for both Android and iOS.

● Build features involving APIs, real-time updates, chat, notifications, local storage and data synchronisation.

● Develop scalable and maintainable mobile architecture with strong focus on performance, reliability and code quality.

● Develop scalable and maintainable mobile architecture with strong focus on performance, reliability and code quality.

● Work closely with Product, Design and Backend teams to translate requirements into simple, effective mobile experiences. 

● Diagnose and resolve performance issues, crashes, bugs and production problems.

● Implement secure handling of user data, authentication and API communication.

● Write unit, integration and UI tests and contribute to reliable release processes.

● Own features end-to-end, from understanding requirements and development through testing, release and iteration.

● Use AI coding tools to accelerate development, debugging, testing, code reviews and technical problem-solving.

● Proactively identify technical challenges and recommend practical solutions. 

What We're Looking For :

● 5 to 6 years of hands-on mobile application development experience.

● Strong professional experience with React Native and TypeScript.

● Mandatory: Experience building and maintaining applications for both Android and iOS.

● Strong understanding of React Native architecture, mobile app lifecycle, state management, API integration and performance optimisation.

● Experience working with REST APIs, authentication, local storage, push notifications and asynchronous data flows.

● Experience debugging and resolving Android/iOS-specific issues and production bugs.

● Good understanding of mobile security, data handling and secure API communication.

● Experience using AI-assisted development tools such as Cursor, Claude Code, GitHub Copilot or similar to improve engineering productivity.

● Strong problem-solving skills with the ability to independently own and deliver features.

● Good product thinking and attention to detail. 

Good to Have :

● Experience with chat, voice, video or real-time communication features.

● Experience building AI-powered mobile experiences or integrating AI/LLM-based features.

● Experience with mobile analytics, crash monitoring and performance monitoring.

● Familiarity with CI/CD and automated mobile releases.

● Experience working on healthtech, consumer apps or products handling sensitive user data. 

Job Title : Full-Stack AI Product Engineer

Experience : 3+ Years

Work Mode : Remote

Time Zone : IST

Engagement Type : Freelance

Availability : Must be comfortable attending US client calls during IST night hours.

Role Overview :

We are looking for a Full-Stack AI Product Engineer with hands-on experience building and deploying production-ready AI-powered applications. The ideal candidate should have strong Python backend development skills, practical expertise in LLMs, AI agents, RAG pipelines and tool calling, along with basic frontend development knowledge.

Mandatory Skills :

Python, FastAPI, AI / LLMs, AI Agents, RAG, Tool Calling, PostgreSQL, Redis, Docker, GCP / Cloud Run, CI/CD, Basic React.js / Next.js.

Key Responsibilities :

• Design, develop and maintain AI-powered products using Python and FastAPI.
• Build and integrate LLM-based applications, AI agents, RAG pipelines and tool-calling workflows.
• Develop scalable backend services and REST APIs.
• Work with PostgreSQL and Redis for data storage, caching and performance optimization.
• Containerize applications using Docker and deploy services on GCP, preferably Cloud Run.
• Implement CI/CD pipelines and follow production deployment best practices.
• Develop and integrate basic frontend features using React.js or Next.js.
• Troubleshoot production issues, optimize performance and ensure application reliability.
• Collaborate with US-based clients and stakeholders during IST night hours when required.

Required Skills :

• 3+ years of relevant software development experience.
• Strong proficiency in Python and FastAPI.
• Hands-on experience with AI / LLMs and production-level AI product development.
• Practical experience building AI agents, RAG pipelines and tool / function-calling workflows.
• Good knowledge of PostgreSQL and Redis.
• Experience with Docker, GCP / Cloud Run and CI/CD pipelines.
• Basic working knowledge of React.js or Next.js.
• Understanding of REST APIs, application architecture, deployment and production debugging.
• Excellent problem-solving and communication skills.

Preferred Qualifications :

• Experience deploying and maintaining AI applications in production.
• Familiarity with LLM orchestration frameworks and vector databases.
• Experience with cloud-native application development and monitoring.

Important Requirements :

• Must have demonstrable, hands-on experience delivering production-grade AI products.
• Must be comfortable working remotely and coordinating with US clients during IST night hours.

Designation: AI Adoption specialist/AI Consultant

Location: Ahmedabad

Work Timings: Primarily Normal Shift (Flexible to support US clients)

Role Overview:

We are seeking a highly skilled and client-centric AI Consultant/AI Adoption Specialist to join our growing team. In this pivotal role, you'll serve as a vital link between our clients' strategic objectives and the transformative power of AI. You'll primarily focus on understanding their needs, scoping opportunities, and architecting actionable AI roadmaps.

Key Responsibilities:

 Collaborate closely with clients to understand their challenges and identify opportunities to apply AI.

 Assess client requirements and prepare solution strategies using AI tools and methodologies.

 Work with internal teams to design, propose, and help execute AI-powered solutions.

 Provide AI-based recommendations that align with the client’s business objectives.

 Communicate technical possibilities in a business-friendly manner to decision-makers.

 Take ownership of the client journey from discovery to implementation and support.

 Stay updated with AI trends, tools, and real-world use cases that can benefit clients.

Required Skills & Qualifications:  Minimum 2+ Years of hands on experience into Custom AI Development.  Minimum 3+ years of experience in roles like Project Manager, Customer Success Manager, or Account Manager, preferably in a service-based company or digital agency.  Strong understanding of AI concepts, trends, and tools (e.g., NLP, ML, Chatbots, Automation, native cloud technologis).  Some hands-on experience in AI projects – either through execution, coordination, or implementation.  Ability to manage multiple client engagements and communicate effectively with both technical and non-technical stakeholders.  Strong problem-solving mind set with the ability to translate business needs into AI opportunities.  Flexible to work with international clients, especially in the US time zone as needed.

About Juicelabs

Where creative engineering meets applied AI.

We build vertical, AI-native tools that unlock fresh insights and creative superpowers for clients in advertising, ecommerce, and beyond. We're a nimble team of founders and builders obsessed with using AI to solve real problems in ways that didn't exist eighteen months ago.

The Opportunity

A year ago, we would have posted this as a backend role. That role doesn't really exist any more.

Code has become nearly invisible. Agents write it, test it, and iterate on it faster than anyone could read it. What's left is the work above it: deciding what's worth building, designing systems that hold up at 10x, and building the setup that turns a clear spec into working software.

That's the job. At your level, it isn't one system. It's several workstreams, running at once.

You'll work directly with our Cofounder/CTO on products going from zero to one, with AI at the core of both what we build and how we build it. Real ownership, real scope, and an unusual amount of leverage: one engineer with good judgment and a well-tuned agent setup now ships what a small team used to.

What you'll do

• Own multiple workstreams in parallel. Two or three features of the same product moving at once, each with its own scope, edge cases, and failure modes. You decide where your attention goes this week, and nothing goes stale.
• Run a fleet, not a single agent. Design the setup that makes high-throughput work possible: how work gets broken down, specced, and run across many agents at once, so output scales without things breaking.
• Design the system. Service boundaries, data models, failure modes. Make the architectural calls before a line gets generated, and be able to explain the trade-off six months later.
• Write the spec. PRDs and technical designs are the new source code. A vague spec produces confidently wrong software, fast. Scope, edge cases, non-goals, what "done" means.
• Own it end to end. Ideation → design → build → deploy → monitor → iterate, including functional UX. Nobody hands you tickets.
• Set the workflow. Bring your harness: CLAUDE.md, AGENTS.md, subagents, custom commands, eval loops — whatever makes agents reliable rather than merely impressive. We want to steal your good ideas.

What we're looking for

• High agency. You see the gap and close it. You don't wait for direction, and you don't need to be chased for follow-through. This is the single trait we screen hardest for. And you can do it across several workstreams at once, without dropping threads.
• Real system design depth. You can reason about consistency, caching, queues, and scale — and about complexity, because you need to know when an elegant-looking solution is quietly quadratic. LeetCode ninja not required. Being able to explain why this won't blow up at 10x, very much required.
• Clear thinking, put to paper. You get the thinking straight first, then write it down so nobody has to guess: PRDs, design docs, PR comments. Writing is most of how you'll direct both humans and models, and muddy thinking on paper becomes muddy software.
• You've shipped to production. Deployed things, monitored them, been paged by them, fixed them. Docker, CI/CD, cloud infra. Our stack is mostly Python (FastAPI), Postgres, GCP/AWS — but we care more about how you think than which framework you've memorised.
• You orchestrate AI, not just use it. Not "I've tried Copilot," and not just "I use Claude Code." You've run multiple agents in parallel and developed opinions: how to split work so they don't step on each other, where they excel, where they confidently lie, how you structure a repo so they don't wander, and how you verify what comes back at volume.
• Startup energy. Multiple hats, fast cycles, and the judgment to balance "ship it now" against "will this survive contact with real users?"

Experience

3–6 years of professional experience (full-time positions, excluding internships).

Location / How to apply

On-site at our office in HSR Layout, Bangalore.

Apply through this posting, or email us with a link to the best thing you've built.

Job Overview

We are looking for an experienced AI/ML Engineer with strong full-stack development skills to design, develop, and deploy AI-powered applications. The ideal candidate should be proficient in Python backend development, frontend technologies, and LLM integration, with the ability to build end-to-end AI-native products, custom dashboards, and lightweight applications.

This role focuses on applying AI to real-world business problems through rapid prototyping, prompt engineering, Retrieval-Augmented Generation (RAG), and scalable application development.

Key Responsibilities

• Design, develop, and deploy end-to-end AI-powered applications.
• Build backend services and REST APIs using Python.
• Develop responsive frontends using React, Next.js, or similar frameworks.
• Integrate LLM APIs such as OpenAI, Claude, and Hugging Face into production applications.
• Build custom dashboards, internal tools, micro-apps, and AI-driven business solutions.
• Implement prompt engineering, embeddings, RAG pipelines, and context-aware AI systems.
• Rapidly prototype and validate ideas using modern AI-assisted development workflows.
• Optimize application performance, scalability, reliability, and AI usage costs.
• Work with data processing libraries such as Pandas and NumPy.
• Collaborate with product and business teams to translate requirements into functional AI solutions.
• Take ownership of features from ideation and development through testing, deployment, and production support.

Required Skills & Qualifications

• 2+ years of experience in software engineering, AI engineering, or application development.
• Strong proficiency in Python and backend development.
• Hands-on experience with React, Next.js, or similar frontend technologies.
• Practical experience integrating LLM APIs such as OpenAI, Claude, or Hugging Face.
• Understanding of REST APIs, microservices, and system design principles.
• Knowledge of prompt engineering, embeddings, and RAG architectures.
• Experience with data processing using Pandas and NumPy.
• Ability to independently build, test, and deploy full-stack applications.
• Strong problem-solving, debugging, and analytical skills.
• Ability to work in a fast-paced environment with a strong ownership mindset.

Good to Have

• Experience with LangChain, LlamaIndex, or similar AI frameworks.
• Familiarity with vector databases such as Pinecone, Weaviate, or Supabase.
• Experience building AI chat interfaces, copilots, assistants, and custom dashboards.
• Familiarity with cloud platforms, application deployment, and production monitoring.
• Experience with AI-assisted coding tools and rapid prototyping workflows.

What We Are Looking For

• A full-stack AI engineer who is comfortable working across both backend and frontend development.
• Someone focused on building practical AI-powered products rather than only training machine learning models.
• A developer who can prototype quickly, validate ideas, and iterate efficiently using a “vibe coding” approach.
• A self-driven professional who can take ownership of a feature from concept to production.

Please note that this job is only for Ahmedabad location.

Location: Nikol, Ahmedabad, Gujarat

Work Mode: Work From Office

We are looking for an Angular Developer who can understand product problems, work with partial requirements, use AI coding tools effectively, and take ownership of delivery.

This is a frontend-focused role, but you must have a good understanding of how the complete application works - frontend, APIs, backend, authentication, data flow, and production behaviour.

What We Need

• Good knowledge of Angular, TypeScript, JavaScript, Bootstrap 5, HTML and CSS
• Understanding of components, services, forms, routing and RxJS
• Experience with REST APIs / WebSockets
• Good understanding of frontend-to-backend flow
• Ability to identify whether an issue is frontend, API, backend, or data related
• Good debugging and problem-solving skills
• Ability to understand an existing codebase quickly
• Responsive and reusable UI development
• Git and deployment workflow knowledge
• Ability to test your own work before sending it to QA

AI-Enabled Development

We actively use AI coding tools such as Claude Code and provide the required subscriptions.

You should know how to use AI for:

• Understanding requirements
• Research
• Understanding existing code
• Technical planning
• Creating documentation
• Preparing feature/user flows
• Creating prototypes or proof of concepts
• Implementation
• Debugging
• Testing
• Code review

We do not want someone who only gives prompts to AI and waits for the answer.

You should be able to:

• Give proper context to AI
• Break problems into smaller tasks
• Validate AI-generated code
• Identify wrong assumptions
• Improve generated solutions
• Work on multiple activities in parallel
• Keep execution moving while AI tools are working

Problem-to-Execution Mindset

In our product team, requirements will not always come as a fully prepared task.

Sometimes you may receive only:

• A customer problem
• A business requirement
• A rough idea
• Partial clarity
• An expected outcome
• 
  

Your responsibility is to help convert that into something executable.

You should be able to:

Understand → Research → Ask Questions → Create Flow → Document → Prototype if Needed → Implement → Test → Verify

We are looking for people who can gradually prepare the solution, not only execute a ready-made task.

Product & Ownership Mindset

We are a product-based company.

You should understand:

• Why a feature is required
• What problem it solves
• How customers will use it
• What backend/API dependencies exist
• Edge cases and failure states
• Production impact

You should take responsibility for the complete outcome of your work.

Expected ownership:

Requirement → Planning → Implementation → Testing → Deployment → Verification → Documentation

Our culture is focused on ownership and outcomes, not simply completing assigned hours.

Flexibility & Delivery

You should be comfortable with:

• Changing priorities
• Working across different modules
• Urgent product requirements
• Learning unfamiliar technologies
• Supporting production fixes when needed
• Delivering some requirements within short timelines
• Taking responsibility for the final result

Future Scope - Agentic AI

Our future direction includes building more AI agents and automated product workflows.

Deep experience is not mandatory today, but you should be willing to learn:

• LLM APIs
• Tool calling
• MCP
• AI agents
• Agent workflows
• Automated operations

What We Value Most



• Strong fundamentals
• Learning speed
• Problem-solving ability
• Effective AI usage
• Product understanding
• Backend/API awareness
• Parallel execution
• Flexibility
• Quality
• Ownership
• Ability to grow into a Feature Owner / Product Owner

This role may not be suitable for candidates who expect fully prepared tasks, step-by-step instructions, or continuous dependency on senior developers.

Tealbox Digital · Gurgaon · Hybrid, 3 days a week · 5–10 years' experience

₹20–26 lakh fixed + up to 20% variable

Please fill the form to apply: https://forms.gle/zi11r958i7hjneRQA

The bet we're making

Most of what a media buyer does today - building campaigns, structuring accounts, reading reports, spotting the obvious optimisation - is going to be absorbed by AI. Not in five years. Now.

If that's right, the scarce skill in an agency stops being platform expertise. It becomes two things. Knowing what to point the systems at. And being the person a client actually trusts.

We're hiring for that role. You'd own a portfolio of client businesses. You'd run them through an AI layer we're building. You'd be the human accountable for what comes out. Not an account manager who uses AI. Someone whose job is to get far more done per person than the industry thinks possible.

About Tealbox

We're a paid media agency for B2B SaaS and DTC brands, on Meta, Google and YouTube. Accounts run from ₹5 lakh to ₹5 crore a month in ad spend. Small team, serious about the craft. We're working out what an agency should be once the execution gets automated.

What you'd own

• The portfolio. A book of client businesses, end to end. Measured on whether clients stay and grow and on the portfolio's margin - not on what you shipped.
• The client relationship. You're the person they call. You bring a point of view they didn't ask for. You tell them the truth when it's inconvenient. You say no when no is right.
• Quality control at scale. The hard part. Twenty accounts of AI-generated analysis means twenty accounts of plausible-looking output. Some of it is wrong. All of it is spending someone's money. You're the check.
• The AI layer, applied. We build the systems. You decide how they're used on each account. You spot where they're working and where they're producing confident nonsense. You tell us what to build next.
• A small pod. A couple of people plus the systems. You coach them and set how the pod works.

Who we're looking for

Five to ten years in account management, client servicing, performance marketing or growth. We care more about the shape of your judgment than the label on your CV.

• Business judgment. You see what actually drives a client's business. When you see a number, you have an instinct for whether it's plausible before you check.
• Client trust. You've held senior relationships and kept them. You've challenged a client and been right.
• AI fluency you can show. Not "I use ChatGPT." You've changed how you work. You know where the tools break. You've built something other people now use.
• The scepticism to catch a wrong answer. You don't accept confident output because it's well formatted.

On advertising knowledge, read carefully. You need to read performance data with confidence. You need to hold your own with a media buyer. You need to be credible with a client about why performance moved. That's a real bar and we'll test it. You do not need to build campaigns yourself. We think the buying craft moves into the systems. What doesn't move is judgment about whether the output is any good. If you're a strong media buyer who wants to keep building campaigns, this job will frustrate you.

Compensation

Fixed: ₹20–26 lakh a year, depending on experience. Variable: up to 20% of fixed, paid twice a year. Three targets: client retention in your portfolio, portfolio margin, and accounts under management.

Why this is worth your time

• You'd be early on the thing everyone's about to do. Every agency will claim to be AI-native within two years. You'd have actually done it, with proof.
• Your output is your market value. If you can run twenty-five accounts where a peer runs six, you're worth several times that peer in the market. The variable is built to reflect that. This role makes you more valuable, not more locked in.
• Direct line to the founder building the system you use. Your feedback goes straight to the person building it.

The honest version

• The AI layer runs on a few accounts today. It's being expanded. Some of what you need will be ready when you join. Some won't. You'd shape it from real problems.
• The ramp is real. You start with five to eight accounts, not twenty. Twenty to thirty is where this goes within a year, if the systems deliver. That's the direction, not the starting line.
• Gurgaon-based, hybrid, three days a week in office; days agreed with Varun.
• We work to the outcome. When a client outcome, a launch or a live problem needs attention outside normal hours, we deal with it. That expectation grows with seniority. Three things come with it. Your manager owes you recovery time after a heavy stretch. Anything that causes repeated out-of-hours work gets fixed as a process problem, not absorbed. And nobody here measures commitment by response time at midnight.
• We're mid-repair. We're a founder-led business fixing how it manages people. You'd be joining during, not after.
• Nobody has done this job before. Including us.

How we'll hire

Four rounds, quick, and you'll know where you stand at every step.

1. Track record and business judgment: A conversation.
2. Assignment: A three-hour take-home exercise.
3. Client leadership: Assignment discussion and a live client role-play.
4. Values and ways of working: A two-way conversation.

If this sounds like the kind of challenge you’d enjoy, we’d love to hear from you.

Laravel Developer – Education ERP

Experience: 2 years

Work Mode: Permanent Work From Home

Job Summary

We are looking for an experienced Laravel Developer with strong expertise in Core PHP, Laravel, and MySQL to develop, maintain, and optimize scalable Education ERP applications.

Key Responsibilities

• Develop and maintain ERP modules such as HRMS, Admissions, Fees, Examinations, LMS, Inventory, and Finance.
• Write clean, secure, and efficient code using Laravel and Core PHP.
• Design and optimize MySQL databases, complex SQL queries, and bulk data processing.
• Develop and integrate REST APIs and third-party services.
• Troubleshoot bugs and optimize application performance.
• Collaborate with the team to deliver scalable and reliable ERP solutions.

Required Skills

• Strong knowledge of Laravel, Core PHP, and MySQL.
• Experience with MVC architecture, Eloquent ORM, CRUD operations, and REST APIs.
• Good understanding of SQL joins, database optimization, HTML, CSS, JavaScript, and jQuery.
• Familiarity with Git/GitHub and web application security.

Preferred Experience

• Experience developing Education ERP or university management software.
• Knowledge of HRMS, Fees, Admissions, Examinations, and LMS modules.
• Experience handling large datasets and enterprise applications.

 Hiring: SEO Executive (Night Shift)

📍 Location: Sector 63, Noida

⏰ Shift Timings: 8:00 PM to 5:00 AM (Mon–Fri)

Cab Facility : Provided ( One side )

💼 Job Type: Full-time | On-site

📅 Experience: 1–3 Years

Salary: Hike On Current

📌 Key Responsibilities

On-Page & Off-Page SEO: Keyword research, meta tags, content optimization, and link building.

Technical SEO: Conduct site audits, improve speed/indexing, fix crawl errors, and implement schema markup.

Analytics & Reporting: Track performance using Google Analytics, Google Search Console, Ahrefs, SEMrush, and Screaming Frog.

Competitor & Market Analysis: Monitor rankings, backlink profiles, and stay updated with search engine algorithm updates.

🎯 Requirements

Proven experience as an SEO Executive / Specialist.

Comfortable working fixed night shifts (8 PM - 5 AM).

Hands-on experience with standard SEO & Analytics tools.

Strong written & verbal English communication skills.

🎁 Perks: Night shift allowances + Fixed weekends off (Sat-Sun) + Excellent growth opportunity.

Role & Responsibilities

• Own end-to-end architecture, system design, development, and production deployment of scalable, AI-powered applications.
• Architect and develop high-performance backend services using Node.js, NestJS, TypeScript, Express.js, and Go.
• Design scalable web applications using React.js and Next.js, and cross-platform mobile applications using Flutter and Dart.
• Design distributed systems, microservices, event-driven architectures, and real-time applications capable of handling massive data volumes and high concurrent traffic.
• Design and optimize PostgreSQL/MySQL databases, MongoDB, Redis caching, database indexing, transactions, and query performance.
• Build real-time ride-booking, driver-allocation, location-tracking, and proximity-based matching systems using geospatial technologies such as PostGIS.
• Design and implement REST APIs, WebSockets, secure authentication, authorization, RBAC, and third-party integrations.
• Build and integrate Generative AI applications, LLM-powered chatbots, AI agents, RAG pipelines, embeddings, vector databases, tool calling, and intelligent automation workflows.
• Develop AI and backend services using Python and integrate LLM platforms such as OpenAI, Claude, and Gemini.
• Architect secure payment integrations, transaction workflows, webhook processing, idempotency, and payment reconciliation.
• Design and implement cloud-native infrastructure using AWS, Docker, CI/CD pipelines, and production monitoring tools.
• Ensure application security, scalability, reliability, performance, maintainability, and cost efficiency.
• Lead technical decision-making, code reviews, debugging, performance optimization, documentation, and mentoring of developers.
• Independently own critical engineering deliverables and drive products from concept and architecture through development, testing, deployment, and production support.

Preferred Candidate Profile

• 710+ years of software development experience, with substantial hands-on experience in technical architecture and production-grade application development.
• Expert-level proficiency in Node.js, NestJS, TypeScript, REST APIs, backend architecture, and microservices.
• Strong experience with React.js, Next.js, and modern frontend architecture.
• Hands-on experience with Flutter and Dart for Android and iOS application development.
• Proven experience designing scalable systems, handling large data volumes, concurrent workloads, and performance-critical applications.
• Strong experience with PostgreSQL, database design, indexing, query optimization, transactions, Redis, and geospatial systems.
• Practical experience building and deploying LLM-powered applications, AI agents, RAG systems, embeddings, vector search, and AI workflow automation.
• Proficiency in Python for AI integrations and backend services; Go language experience is highly desirable.
• Strong understanding of authentication, authorization, application security, payment integrations, and secure API design.
• Hands-on experience with AWS, Docker, CI/CD, Git, production deployments, logging, and monitoring.
• Familiarity with Kafka/RabbitMQ, Kubernetes, LangChain/LlamaIndex, and event-driven architectures is an advantage.
• Exceptional system-design, analytical, debugging, and problem-solving skills.
• Strong ownership, independent execution, technical leadership, communication, and mentoring abilities.
• Experience in startups or building products from scratch is highly desirable.

What We Expect

We are looking for a highly hands-on technical leader who can independently architect, design, develop, optimize, and deploy complex production systems. The ideal candidate must demonstrate genuine technical depth, strong engineering judgment, and the ability to lead end-to-end product development across backend, web, mobile, cloud, and AI technologies.

Education: B.E. Computer Science/IT degree (or any other engineering discipline)

Experience: 9+ years

 Work timings: 2:00 TO 11:00PM/ 6:30PM to 3:30 AM

Position Requirements:

• Program Strategy & Planning
• Own program charters, end-to end roadmaps, success criteria and alignment to business objectives.
• Translate company strategy into clear program priorities, milestones, and resource plans across multiple teams.
• Lead quarterly and long-range capacity planning, balancing scope, resources and timelines across workstreams.

•          Program Execution & Delivery

• Drive delivery of large, technically complex programs comprising multiple projects and teams; ensure on-time, high-quality outcomes.
• Orchestrate cross-functional dependencies, manage sequencing, and remove organizational impediments.
• Operate program-level release, milestone and launch processes; maintain program schedules and integrated plans.

•          Technical Leadership & Influence

• Maintain technical fluency across systems (APIs, services, data, infra, web and mobile platforms) to identify risks, trade-offs, and integration concerns.
• Partner with engineering leads and architects to surface technical dependencies, propose solutions, and influence technical direction.
• Lead technical intake, prioritization and change control for program scope.

•          AI Programs & Governance

• AI-specific program accountability: Own model lifecycle programs (experimentation → validation → deployment → monitoring → scale), model risk management, and coordination with MLOps and data science teams.
• Governance and control: Implement and maintain governance for clinical, editorial, regulatory, and AI-specific risks (bias, explainability, monitoring), coordinating policies and controls with legal, compliance, and domain stakeholders.
• Offshore reality: Design and operate for distributed teams—ensure timezone overlap strategies, clear escalation mechanics, minimize decision latency, and define RACI for offshore/onshore handoffs.
• Experience in mentoring engineering teams to integrate AI assistants into their daily development workflows to increase velocity and code quality.

•          Stakeholder Management & Communication

• Serve as primary program owner for senior leadership and business partners; run steering committees and executive reviews.
• Produce concise executive-level reporting (status, risks, mitigation, outcomes) and tailor communications for diverse audiences.
• Build strong cross-functional relationships and drive alignment through regular touchpoints and stakeholder feedback loops.

 •          Risk, Budget & Vendor Management

• Develop and maintain program-level risk registers, contingency plans, and escalation protocols.
• Manage program budgets, track spend vs. plan, and coordinate with finance and procurement as needed.
• Own vendor/third-party integration and delivery where applicable.

•          Process, Tools & Automation

• Establish program governance, templates, and tooling conventions to improve visibility and efficiency.
• Identify automation and tooling opportunities (including AI-assisted tooling) to reduce manual work and improve program telemetry.
• Drive PMO maturity: scalable processes, reporting, and knowledge management across the organization.

•          Measure Impact

• Define and track program success metrics and business outcomes; iterate to maximize value delivery.
• Ensure learnings are captured and operationalized for future programs.

Role & Responsibilities:

• 10+ years of program or technical project management experience delivering large-scale technical programs in fast-paced, matrixed organizations.
• Proven track record driving multi-team, cross-functional technical initiatives from concept to measurable business outcomes.
• Strong technical literacy (experience with APIs, backend services, cloud infrastructure, data flows and integrations).
• Advanced proficiency with Agile at scale methodologies (e.g., SAFe, LeSS, or equivalent) and deep SDLC knowledge.
• Experience with capacity planning, roadmaps, dependency management, and cross-team prioritization.
• Expert-level proficiency in JIRA and Confluence; comfortable with program/portfolio tooling (Aha!, Productboard, Roadmunk, Airtable, Smartsheet, BI dashboards).
• Excellent stakeholder management and executive communication skills; proven ability to influence without direct authority.
• Strong analytical and problem-solving skills; data-driven mindset.
• Bachelor's degree in Computer Science, Engineering, or equivalent experience.
• Fluent English.

•          Preferred

• Certifications such as PMP, CSM, SAFe Program Consultant (SPC), or equivalent.
• Experience in digital publishing, web/content platforms, AI/ML products, healthcare information systems, or digital media.
• Experience managing program budgets and vendor/contract relationships.
• Familiarity with emerging project automation and Agentic AI tools for program management and decision support.
• Prior experience mentoring PMs and leading PMO or program-level process change initiatives.