4,151 Python Jobs in India

Staff Engineer – Automation & Manual Testing

Company: Stryker

Industry: Medical Devices / Healthcare Technology

Location: Gurugram– Onsite

Experience: 5–10 Years

Employment Type: Full-Time

Required Skills & Qualifications

• 4–10 years of experience in Software Testing, covering both Automation and Manual Testing.
• Strong hands-on experience in Automation Framework Development – Mandatory.
• Strong programming experience in either Java or Python.
• Hands-on experience with one or more of:
• Selenium
• PyTest
• Cucumber
• Java/Python-based automation frameworks
• Experience in designing, developing, maintaining, and enhancing automation frameworks.
• Strong understanding of Manual Testing, including test case design, execution, regression, exploratory testing, and defect verification.
• Good knowledge of SDLC, STLC, testing methodologies, defect lifecycle, and risk assessment.
• Experience with version control and defect/bug tracking tools.
• Good understanding of Agile/Scrum methodologies.
• BE/B.Tech/ME/M.Tech in Computer Science, Information Technology, Electronics, Electrical Engineering, or a related engineering discipline.

Preferred Skills

• Experience working with both Java and Python.
• Experience with Linux, Qt/QML, or Squish.
• Exposure to performance/non-functional testing.
• Experience in regulated or compliance-driven product development environments.
• Experience in the medical devices/healthcare domain.
• ISTQB, CSM, PSM, or other relevant certifications.

What We're Looking For

• Strong automation engineers who have built or significantly enhanced automation frameworks, rather than only executing existing scripts.
• Candidates with solid hands-on coding experience in Java OR Python.
• Professionals comfortable working across both automation and manual testing.
• Strong problem-solving, debugging, and collaboration skills.
• Candidates who can contribute to test strategy as well as hands-on implementation.

Share CV at : snigdhaattheratebeanhr.com

Data Engineer Short Hiring Post

🚨 Hiring: Data Engineer

🔹 Experience: 5–9 Years

🔹 Location: Bangalore / Hyderabad

🔹 Skills: PySpark, Python, SQL, ETL, CI/CD, Data Modeling

🔹 Process: L1 Virtual → L2 F2F Karat Test

🔹 F2F: Bangalore / Hyderabad Location

🔹 Positions: Immediate requirement

⚠️ Note: Candidates must be available for F2F Karat immediately after L1.

#Hiring #DataEngineer #PySpark #Python #SQL #BangaloreJobs #HyderabadJobs #Mphasis #ImmediateJoiners

• Design and implement scalable IoT solutions from sensor to cloud, ensuring seamless integration between

vehicle hardware (fuel sensors, GPS trackers, OBD devices) and the Anytime Diesel platform

• Integrate industrial and automotive sensors, microcontrollers, and gateways with the platform

• Develop, optimize, and troubleshoot data flow using protocols such as CAN bus, Modbus, RS485, TCP, and

RTU

• Manage the full IoT device lifecycle across the fleet — provisioning, remote configuration, health monitoring,

and OTA/FOTA firmware updates

• Collaborate with software, data, and operations teams to define data models and ensure clean data ingestion for

fleet analytics

• Conduct testing, debugging, and performance analysis of embedded firmware and IoT systems using tools like

oscilloscopes and logic analyzers

• Create technical documentation — architecture diagrams, API specs, and deployment guides

Core Responsibilities

Operational Tools Architecture & Feature Planning 

• Own the feature roadmap for operational tools — Odoo, Redmine, GitHub, and adjacent systems — from business-process discovery through design, planning, and phased delivery 
• Serve as the subject-matter expert on how business processes (deal onboarding, delivery, support, finance, engineering operations) map onto tool capabilities, and where the gaps are 
• Design cross-tool workflows and integrations so that work items, code, and business records flow between systems as one coherent operational fabric 

Agentic Implementation & Modernization 

• Design agent-operable surfaces on each tool: typed, secure APIs, Model Context Protocol (MCP) servers, and webhook-driven automation that let AI agents read, create, and resolve operational work safely 
• Lead incremental modernization of legacy tool deployments — upgrading versions, retiring brittle customizations, and replacing manual processes with agentic workflows without disrupting live operations 
• Optimize agentic loops that operate on the tools for cost, speed, and integrity, with guardrails, audit trails, and human-in-the-loop checkpoints where they matter 

Plugin & Extension Engineering 

• Architect and build Redmine plugins in Ruby on Rails, Odoo modules, and GitHub Apps/Actions that extend the products cleanly rather than forking them 
• Engineer enhancements to be upgrade-safe across product versions — tracking upstream releases, isolating customizations behind stable interfaces, and planning migration paths 
• Prioritize contract-first API design between human intent, agent execution, and the underlying tools 

Governance & Quality Control 

• Act as the architectural reviewer for changes to Central tooling, including AI-generated pull requests and agent-authored configuration 
• Mandate testing and characterization coverage around customizations so upgrades and agentic changes land deterministically 
• Establish operational standards — access, data integrity, observability — for agents acting inside business-critical systems 

Required Qualifications 

• 10+ years in software engineering, business-systems architecture, or platform engineering, with deep SME knowledge of operational tools such as Odoo, Redmine, GitHub, or comparable ERP/ITSM/DevOps platforms 
• Expert-level proficiency in Ruby on Rails, including production experience building or maintaining Redmine plugins or comparable Rails-based extensions 
• Strong command of business processes across delivery, support, and operations — able to translate how a business runs into how a tool should behave 
• Practical agentic development experience: MCP, LLM tooling, AI-assisted automation, or agent-orchestrated workflows in production 
• Proven track record building plugins, modules, and extensions that survive product version upgrades, with disciplined API and integration design 
• Commitment to clean, tested, production-grade systems — including when the author of the code is an agent 

Preferred Qualifications 

• Python and Odoo module development experience; PostgreSQL fluency 
• Experience modernizing or migrating legacy tool deployments across major versions 
• Background in SaaS transformation, scale-up, or PE-backed environments 

Job Summary:

Wissen Technology is hiring an AI Implementation Engineer to build, deploy, and scale enterprise-grade Generative AI solutions across business-critical applications. The role involves developing production-ready AI systems using Azure AI services, Large Language Models (LLMs), RAG architectures, and agent-based frameworks while collaborating closely with engineering teams to drive AI adoption and innovation.

Experience

6-12 years

Location

Mumbai / Bangalore

Mode of Work

Hybrid

Mandatory Skills (Must Have)

• Python programming (6+ years) including asynchronous programming and backend application development

• Java and Spring Framework (3+ years) for enterprise-scale application integration

• Azure OpenAI Service, Azure AI Foundry, and Azure AI Search for production GenAI applications

• Retrieval Augmented Generation (RAG) architecture including embeddings, chunking, vector databases, reranking, and grounding techniques

• Agent Frameworks such as Microsoft Agent Framework, Semantic Kernel, AutoGen, LangChain, or LangGraph

• Snowflake and Cortex AI (Cortex Search, LLM Functions) with strong SQL expertise

• Prompt Engineering, LLM evaluation frameworks, testing, and model performance optimization

• DevOps and Cloud Deployment using Azure DevOps, GitHub Actions, Docker, AKS, Azure Functions, and observability tools

Optional Skills (Good to Have)

• React.js for AI-powered user interfaces and conversational applications

• Azure AI Content Safety and Responsible AI implementation experience

• Financial Services, Banking, or other regulated industry domain experience

• Real-time streaming applications and token-level LLM operations

• Performance optimization, caching strategies, and cost optimization for AI workloads

• Microsoft Azure AI Engineer Associate Certification

🚨 Hiring: .NET Full Stack Developer | .NET + Angular

We are hiring experienced .NET Full Stack Developers for an exciting opportunity with Mphasis!

🔹 Experience: 5–7 Years

🔹 Positions: 2

🔹 Location: Bangalore / Hyderabad

🔹 Skills: .NET + Angular

🔹 Interview Process:

  • L1 – Discussion

  • L2 – Karat Test (Face-to-Face)

🔹 Karat F2F Location: Mphasis Office – Bangalore / Hyderabad

⚠️ Important Note:

Only candidates who are immediately available for the Face-to-Face Karat Test after the L1 discussion will be scheduled.

#Hiring #DotNetDeveloper #DotNet #Angular #FullStackDeveloper #DotNetFullStack #Mphasis #BangaloreJobs #HyderabadJobs #ITJobs #TechJobs #HiringNow #KaratTest #ImmediateAvailability

Title: AI/ML Test Engineer – GenAI

Location - Mumbai

Technical Skills

• Strong experience in Generative AI, LLMs, and Agentic AI systems

• Hands-on expertise with AI evaluation frameworks (RAGAS, DeepEval, TruLens, LangSmith, Promptfoo, etc.)

• Proficiency in Python and AI/ML development libraries

• Knowledge of Prompt Engineering, prompt testing, and optimization

Ability to define and track evaluation metrics such as accuracy, relevance, groundedness, hallucination rate, latency, and user satisfaction

• Experience in creating automated evaluation pipelines and benchmarking frameworks

• Strong understanding of AI safety, guardrails, bias testing, and responsible AI practices

• Familiarity with REST APIs, JSON, vector databases, and knowledge retrieval systems

• Experience in A/B testing, human-in-the-loop evaluation, and red teaming

• Strong experience in Manual Testing of AI/GenAI applications, including functional, exploratory, UAT, regression, and end-to-end testing

• Expertise in validating Agent Reasoning, Tool Calling, Workflow Execution, and Response Quality

• Hands-on experience in Automation Testing using Python frameworks

Key Responsibilities

• Design, execute, and automate evaluation strategies for Agentic AI applications.
• Develop evaluation datasets, test cases, and benchmark suites.
• Measure and improve agent performance, reasoning quality, tool usage, and workflow effectiveness.
• Analyze model outputs and identify hallucinations, biases, safety risks, and failure patterns.
• Collaborate with AI Engineers, Product Teams, and Domain Experts to improve agent quality and reliability.
• Generate evaluation reports, dashboards, and actionable recommendations.

The Role

We’re looking for a Senior Applied AI & Data Engineer to become our first dedicated AI and data engineer.

You’ll build conversational AI experiences across web, mobile, and in-store channels while developing the data foundation behind them. You’ll make key technical decisions and own your work through to production.

What You’ll Do

• Build AI assistants using tool calling to work with real product, search, and order systems

• Design guardrails and evaluation sets to ensure AI responses are accurate and safe

• Build real-time and voice-enabled AI experiences

• Improve product data quality through AI-assisted enrichment and review workflows

• Build data pipelines, analytics, and personalisation systems

• Work closely with web and mobile developers and help guide technical implementation

What You’ll Need

• 6+ years of experience building and running production backend systems

• Strong Python skills, plus experience with JavaScript/TypeScript backends

• Experience shipping at least one LLM-powered feature to real users

• Experience with search and relevance

• Experience building data pipelines and analytics stores

• Comfortable deploying and monitoring services on a major cloud platform

• Strong communication skills and the ability to work independently

Nice to Have

• Experience with speech or voice AI

• E-commerce or retail technology experience

• Experience building multilingual products

Job Summary/ Job Opportunity:

This is an excellent opportunity for an ideal candidate with a high level of technical proficiency and meeting the below mentioned criteria -- • Strong experience in Machine Learning, Deep Learning, Generative AI, and Large Language Models (LLMs). • Hands-on experience building and deploying production-grade solutions using Azure OpenAI, OpenAI, LangChain, LangGraph, Semantic Kernel, LlamaIndex, and Agentic AI frameworks. • Strong expertise in Python, API development, microservices, and cloud-native architectures. • Experience designing and implementing RAG solutions, vector databases, embeddings, knowledge retrieval systems, and AI copilots. • Experience with Azure cloud services, MLOps, CI/CD pipelines, monitoring, and model lifecycle management. • Strong understanding of AI governance, responsible AI, security, compliance, and model evaluation frameworks. • Ability to lead technical discussions, provide architectural recommendations, mentor team members, and interact with business stakeholde

Key Objectives and Major Responsibilities:

• Design, develop, and implement scalable AI/ML and Generative AI solutions for enterprise applications. • Lead development of intelligent applications leveraging LLMs, RAG pipelines, AI agents, and document intelligence solutions. • Collaborate with business stakeholders, architects, and product teams to translate business requirements into technical solutions. • Design and optimize data pipelines, vector search solutions, embeddings, and retrieval mechanisms. • Build and maintain REST APIs, microservices, and cloud-native AI applications. • Ensure best practices in coding standards, performance optimization, security, scalability, and maintainability. • Drive AI solution deployment using MLOps practices, CI/CD pipelines, monitoring, and observability frameworks. • Perform code reviews, mentor junior developers, and contribute to capability building within the team

Key Capabilities and Competencies:

Knowledge, Skills, Qualification and Experience

• Degree in B.Tech/M.Tech (Computer Science/IT/Data Science) or related discipline preferred, with 3–4 years of relevant experience in AI/ML, GenAI and total 5-7 years of experience. • Proficiency in Python and hands-on experience with ML libraries (scikit-learn, TensorFlow, PyTorch) and GenAI frameworks/tools. • Strong understanding of machine learning, deep learning, LLMs, prompt engineering, and techniques like RAG and fine-tuning. • Experience with data processing, embeddings, vector databases, APIs, and building scalable AI driven applications. • Good communication skills, ability to work on multiple projects, and eagerness to learn and adapt to evolving AI technologies. 

Job Description: Tech Lead – AI & Technology

Role Title: Tech Lead – AI & Technology

Location: Bangalore, India – Fully On-site

Experience: 5+ Years

Employment Type: Full-time

About the Role

We are looking for an experienced and hands-on Tech Lead to lead a small engineering team and drive the development of AI-powered applications, internal technology platforms, and modern IT solutions. The Tech Lead will be responsible for technical direction, architecture, development, code quality, team management, and end-to-end delivery of technology projects. The ideal candidate should have strong programming experience, particularly in Python and ReactJS, along with practical experience working with AI/ML technologies.

1. Technical Leadership & Team Management

• Lead and mentor a team of developers and technical team members.
• Own technical delivery across multiple projects and initiatives.
• Assign tasks, review progress, resolve technical blockers, and ensure timely delivery.
• Conduct code reviews and establish engineering best practices.
• Mentor team members and support their technical growth.

2. Software Development & Architecture

• Design and develop scalable, secure, and maintainable applications.
• Lead backend development using Python and frontend development using ReactJS.
• Define application architecture, technology choices, APIs, integrations, and development standards.
• Review technical designs and ensure high-quality implementation.
• Troubleshoot complex technical issues and drive effective solutions.

3. AI & Technology

• Lead the development and integration of AI-powered applications and solutions.
• Work with AI/ML models, APIs, LLMs, Generative AI, and related technologies.
• Evaluate emerging AI tools and technologies and identify opportunities for practical implementation.
• Collaborate with product and business teams to translate requirements into AI-enabled technology solutions.

4. Project Delivery

• Own the complete technology lifecycle from requirements and architecture to development, testing, deployment, and maintenance.
• Plan sprints, estimate development efforts, and track technical milestones.
• Work closely with cross-functional stakeholders to understand requirements and deliver solutions.
• Ensure projects meet timelines, quality standards, security requirements, and performance expectations.

5. Engineering Quality & Infrastructure

• Establish standards for coding, testing, documentation, version control, and deployment.
• Ensure applications are scalable, reliable, and secure. l Collaborate on cloud infrastructure, APIs, databases, CI/CD, and deployment processes.
• Identify opportunities to improve system performance and engineering efficiency.

Technical Skills – Must Have

• 5+ years of software development experience.
• Strong hands-on experience with Python.
• Strong experience with ReactJS / React.
• Experience leading or managing technical team members.
• Strong understanding of AI/ML and Generative AI technologies.
• Experience with APIs, databases, Git, and software development lifecycle.
• Strong understanding of application architecture and system design.
• Experience building and deploying production-grade applications.

Technical Skills – Good to Have

• Experience with LLMs, RAG, AI agents, or Generative AI applications.
• Experience with cloud platforms such as AWS, Azure, or GCP.
• Experience with Docker, CI/CD, and DevOps practices.
• Experience integrating third-party AI APIs and services.
• Experience working in startups or fast-paced technology environments.

What We Are Looking For

• Strong technical ownership and problem-solving ability.
• Ability to balance hands-on coding with team leadership.
• Excellent communication and stakeholder management skills.
• Ability to mentor developers and drive accountability within the team
• Strong interest in AI and emerging technologies.
• A proactive, ownership-driven approach with the ability to work in a fast-paced environment.

Why Join Us?

• Work on AI-powered technology with meaningful social impact.
• Lead a small, high-ownership technology team.
• Work across AI, software engineering, and modern IT infrastructure.
• Opportunity to shape technology architecture and engineering practices from the ground up.
• Collaborative and fast-moving environment with significant technical ownership.

Job Description:

• Minimum 3+ years of experience in RPA development, particularly with UiPath.
• Proven experience supporting legacy UiPath code and enhancing automation processes.
• Hands-on experience in C# development (especially creating custom Nuggets).
• Strong working knowledge of SQL Server and experience writing complex SQL queries and stored procedures.
• Knowledge of Azure cloud services and how to integrate UiPath automation workflows with Azure components.
• Experience with Python for task-specific scripting and automation.
• Familiarity with DevOps practices for continuous integration and continuous deployment (CI/CD) is a plus.

Roles and Responsibilities:

• Minimum 3+ years of experience in RPA development, particularly with UiPath.
• Proven experience supporting legacy UiPath code and enhancing automation processes.
• Hands-on experience in C# development (especially creating custom Nuggets).
• Strong working knowledge of SQL Server and experience writing complex SQL queries and stored procedures.
• Knowledge of Azure cloud services and how to integrate UiPath automation workflows with Azure components.
• Experience with Python for task-specific scripting and automation.
• Familiarity with DevOps practices for continuous integration and continuous deployment (CI/CD) is a plus.

Technical Skills:

• Strong knowledge of UiPath Studio, Orchestrator, and Robots.
• Experience in REST APIs, SOAP Web Services, and integrating external systems with UiPath automation.
• Familiarity with version control systems (e.g., Git).
• Good understanding of DevOps pipelines, Jenkins, or similar tools is an added advantage.

Hiring for Data Engineer - Delivery Manager

Exp : 10 - 15 yrs

Edu : BE/B.Tech/MCA

Work Loation : Hyderabad

.Roles & Responsibilitie:

Own end-to-end delivery of data engineering programs ensuring alignment with business goals, timelines, and quality standards.

Drive execution across multiple data initiatives within Azure and Databricks environments.

Provide technical leadership in designing and implementing scalable data pipelines using Python, PySpark, and Spark.

Required Skills:

Strong experience with Databricks, PySpark, Python, and Spark.

Expertise in Azure Data Services including ADF, ADLS, and Synapse.

Proven experience in delivery management, stakeholder management, and Agile execution

 DevOps, Cloud Engineering, or related roles  Strong hands-on experience with Microsoft Azure (VMs, App Services, AKS, Storage, Networking, etc.)  Expertise in Azure DevOps (Pipelines, Repos, Boards, Artifacts)  Experience with Infrastructure as Code tools such as ARM, Bicep, or Terraform  Proficiency in scripting (PowerShell, Bash, or Python)  Hands-on experience with containerization and orchestration (Docker, Kubernetes/AKS)  Strong experience with monitoring and logging tools within Azure ecosystem  Good understanding of cloud security, networking, and governance in Azure  Experience in managing production environments and handling escalations 

Job Title: Vice President – Technology (VP Tech)

Company: Timble Technologies Pvt. Ltd

Location: Arjan Garh, New Delhi (On-site)

Experience: 15+ Years

About Timble AI

Timble Glance is a high-growth AI-powered RegTech and enterprise B2B SaaS platform delivering mission-critical solutions to the BFSI sector. Our infrastructure powers 30+ enterprise-grade APIs handling digital identity management, real-time fraud mitigation, automated compliance, and document intelligence. We engineer high-concurrency, resilient systems designed for extreme throughput, sub-second latency, and bank-grade data security.

Role Overview

As the Vice President – Technology, you will be the chief technical strategist and engineering executive driving Timble AI’s technical vision, platform modernization, and AI innovation. You will own the end-to-end architectural roadmap, lead cross-functional engineering pods, and scale high-volume distributed systems that safeguard critical financial data. This role requires an executive who combines boardroom strategic gravitas with deep hands-on engineering credibility, capable of bridging rapid B2B SaaS product iteration with rigorous BFSI regulatory standards.

Key Responsibilities

·       Technology Vision & Architectural Strategy: Define and execute a multi-year engineering roadmap across core product suites (Identity Verification, Fraud Detection Engines, and Document Intelligence), balancing cutting-edge feature delivery with enterprise-grade stability.

·       Large-Scale Platform Engineering: Oversee the architecture and performance of 30+ high-scale APIs, ensuring 99.9% uptime, sub-second latency, fault-tolerant concurrency, and strict "efficiency by design" across multi-tenant cloud environments.

·       AI/ML & Intelligent Engineering: Drive the productionization of proprietary AI/ML and Generative AI pipelines—moving capabilities from experimental R&D into secure, low-latency, scalable BFSI workflows while advancing patent-pending intellectual property (IP).

·       Cloud Architecture & FinOps: Direct cloud economics and infrastructure investments across AWS and GCP, establishing containerization, microservice modularity, automated CI/CD pipelines, and robust disaster recovery frameworks.

·       Information Security & Regulatory Compliance: Enforce bank-grade security protocols, data privacy governance, and industry-mandated regulatory compliance (ISO 27001, SOC2, RBI/BFSI data localization guidelines) to protect sensitive enterprise data.

·       People & Engineering Culture Leadership: Attract, mentor, and scale a world-class engineering organization (from SDE-1 to Principal Architects and Engineering Managers); institute rigorous code reviews, automated testing benchmarks, and clear career ladders.

·       Executive & Stakeholder Alignment: Partner directly with the Founder, C-suite, and Product Leadership to translate complex technological initiatives into clear business outcomes, enterprise client trust, and scalable revenue growth.

Required Qualifications & Experience

·       Experience: 15+ years of progressive software engineering and technology leadership experience, with significant tenure leading engineering organizations in Fintech, RegTech, or high-scale B2B SaaS.

·       Education: B.Tech / M.Tech in Computer Science or related engineering field—Tier-1 institutes (IIT, IIIT, NIT) strongly preferred.

·       Core Technical Mastery: Deep hands-on expertise in no, distributed system design, microservices, asynchronous architectures, API gateways, and relational/NoSQL database engines (PostgreSQL, Redis, MongoDB).

·       Cloud & Infrastructure Rigor: Proven track record architecting enterprise systems on AWS/GCP, utilizing Docker, Kubernetes, Kafka/RabbitMQ, and modern APM/observability stacks.

·       AI Production Track Record: Demonstrated experience successfully deploying, monitoring, and scaling machine learning, computer vision, or NLP/LLM models in latency-critical production environments.

·       Governance & Delivery: Strong command of modern engineering methodologies (Agile, DevSecOps, TOGAF/ITIL principles) with a proven history of managing high-throughput, zero-downtime platforms.

Leadership Attributes

·       Technically Credible Executive: Capable of engaging in deep-dive architectural RFCs with engineering teams while articulating business impact and ROI to board members and enterprise BFSI clients.

·       Builder Mindset: Thrives in high-ownership, agile environments, successfully balancing rapid product velocity with uncompromised software quality and data integrity.

·       Force Multiplier: Focuses on institutionalizing robust engineering practices and developing leadership pipelines rather than relying on individual heroics.

·       https://timbleglance.com          

·       You can visit our website .

Must-have qualifications 6+ years in software engineering, with 2+ years building GenAI/LLM applications in production. Strong Python (incl. async) and Java (the primary enterprise application stack; Spring a plus); solid API and systems design. Azure GenAI hands-on: Azure OpenAI, Azure AI Foundry, Azure AI Search for RAG, Azure AI Document Intelligence (IDP), and Prompt Flow. Agent frameworks: Microsoft Agent Framework / Semantic Kernel / AutoGen (or LangChain / LangGraph) and tool / function calling. RAG fundamentals: embeddings, chunking, vector search, reranking, and grounding. Data platforms: Snowflake including Cortex AI (Cortex Search, LLM functions) and SQL, for accessing and grounding on enterprise data. Prompt engineering as versioned code; building and running evaluations. DevOps: Azure DevOps / GitHub Actions, Docker, AKS / Azure Functions, and observability. Preferred Financial services or other regulated environments. Front-end (React) for AI-assisted UX; streaming and tokenlevel operations. Azure AI Content Safety and responsible-AI practices. Certification: Azure AI Engineer Associate. What success looks like - first 6 to 12 months Multiple GenAI features shipped to production within the embedded delivery pods. Measurable adoption and productivity uplift in the teams you support. Reusable components adopted from the architects' reference framework. Clear contributio

Please note: this is a night shift role. The work runs on Canadian Pacific business hours, which means working nights from India. We are upfront about this because it has to suit your life.

About Nexa Consultancy

Nexa Consultancy Inc is a Surrey, British Columbia (Canada) based company that helps other businesses set up everything they need to run and grow: dashboards, CRM, automation, reporting and marketing. We run our own operations on GoHighLevel, n8n and Make.com and build the same systems for our clients. Because this is ongoing work for our clients, we are looking for long-term people who will grow with us, not short-term contractors. We are hiring a full-time, remote Automation Developer in India to own this stack end to end.

What you will do

• Build, maintain and document automations in n8n and Make.com (lead intake, follow-up sequences, appointment booking, WhatsApp and email notifications, reporting).
• Own our GoHighLevel setup: pipelines, workflows, custom fields, calendars, forms, funnels and integrations.
• Connect tools through REST APIs and webhooks (GoHighLevel, Google Sheets, Gmail, WhatsApp, Meta lead forms, Cloudflare Workers, AI APIs).
• Write small scripts and serverless functions (JavaScript or Python) where a no-code step is not enough.
• Monitor scenarios, fix failures fast, and keep an eye on run quotas and costs.
• Build dashboards and reports so the team can see leads, follow-ups and conversions without asking.
• Turn a plain-English request from the Director into a working, tested automation.

What we are looking for

• 2 to 5 years of hands-on automation or integration work, with real n8n and Make.com scenarios you can show.
• Solid GoHighLevel experience (workflows, pipelines, snapshots, API). Other CRMs are a plus.
• Comfortable with REST APIs, webhooks, JSON, OAuth and debugging failed runs.
• Working JavaScript or Python for custom code steps; SQL or Google Sheets formulas are a plus.
• Clear written English. You will document what you build and explain it to non-technical teammates.
• Self-directed. This is a remote role with a small team; you will own outcomes, not just tickets.

Nice to have

• Cloudflare Workers, Zapier, Airtable, Notion, WhatsApp Business API, Meta or Google Ads integrations, OpenAI or Claude APIs.

Work setup

• Full-time, remote, from India.
• Long-term role. We want someone who stays, learns our clients' businesses and grows with the team.
• Must overlap with Canadian Pacific Time business hours for part of each day; exact schedule agreed at offer.
• Your own laptop, reliable high-speed internet and a smartphone are required.

Compensation

• INR 1,00,000 to 1,50,000 per month, which is INR 12,00,000 to 18,00,000 per year, based on experience. We are hiring for 4 positions.

How we hire

• Short screening call, then a practical exercise (build a small n8n or Make.com scenario), then a final interview with the Director.

Data Science (SME)

FACE Prep is India’s leading employability and industry-aligned education company. For over 17 years, we have partnered with higher education institutions to bridge the gap between academia and industry.

● Worked with 2,000+ colleges and universities across India

● Trained 6+ million students across disciplines

● Market leaders in:

● Employability skills & placement readiness

● Industry-aligned academic papers(credit-bearing)

● Full-scale industry-aligned degree programs with universities

● Pan-India operations, headquartered in Coimbatore

● Young, energetic, mission-driven team

● Fast-growing organization with headcount expected to cross 1,000 employees in the next financial year

At FACE Prep, people are the platform on which outcomes are built.

Position: Data Science (SME)

Location: Coimbatore

Duration: Full-Time

Department: Training & Development

Experience: Minimum 2 Years

Role Description :

The Data Science Subject Matter Expert (SME) is a full-time, on-site role based in Coimbatore. The SME will design and deliver data science curricula, including lectures, hands-on labs, and project-based learning for students preparing for tech careers. Daily responsibilities include creating educational content, developing problem sets and case studies, mentoring learners on data analysis and model-building, and reviewing student work to provide constructive feedback. The SME will collaborate with other trainers and the product team to align content with current industry practices and hiring requirements. The role also involves analyzing learner performance data, refining teaching strategies, and occasionally contributing to workshops, bootcamps, and online learning materials.

Requirements:

• Strong foundation in Statistics and Data Science, with the ability to explain complex concepts clearly and practically.

• Hands-on experience in Data Analytics and Data Analysis, including working with real-world datasets and deriving actionable insights.

• Excellent Analytical Skills for problem-solving, designing assignments, and guiding learners through data-driven decision-making.

• Proficiency in common data science tools and languages (e.g., Python/R, SQL, data visualization tools such as Tableau/Power BI).

• Prior experience in teaching, mentoring, corporate training, or curriculum development is highly beneficial.

• Bachelor’s or Master’s degree in a quantitative field such as Computer Science, Statistics, Mathematics, Data Science, or related discipline.

• Ability to communicate effectively with diverse learner groups and collaborate within a multidisciplinary team.

• Exposure to machine learning concepts, model evaluation, and deployment practices is a plus.

IMMEDIATE JOINERS REQUIRED

Senior AI Engineer

Code Generation, Agent Architecture & LLM Systems

📍 Mumbai (On-site) | Full-time | 5+ years

About the Role:

Unico Connect is an AI-first technology partner that builds custom mobile, web, and AI products for clients across multiple geographies.

We are hiring a Senior AI Engineer for a dedicated client engagement focused on building an AI-powered application builder platform - a product where users describe software in plain English and the system generates, previews, and iteratively refines working code.

The mandatory requirement for this role is hands-on production experience shipping LLM-powered systems with agent architectures, with experience in code generation or developer tooling contexts a strong advantage.

The role is product-focused and deeply hands-on. You will own everything between the user's prompt and correct code landing in the project: the agentic loop, code generation pipeline, context management, evaluation suite, and model cost strategy.

You will work alongside the Senior MLOps Engineer who operationalises the infrastructure around your system, and collaborate closely with backend, frontend, and DevOps engineers.

Responsibilities:

Agent Architecture

Design and own the agentic loop for the platform - request interpretation, planning, tool-calling sequence (read file, edit file, run build, search code, install package), and stop conditions.

Make and revisit architectural decisions on single-agent vs. multi-agent designs, including planner/executor splits and dedicated build-repair sub-agents.

Code Generation Pipeline

Own the end-to-end generation flow: task classification, context gathering, planning, targeted edits, verification, and commit.

Implement diff/search-replace-based file editing with fuzzy matching and fallback strategies.

Enforce scope discipline so the agent makes minimal diffs and does not modify code it was not asked to touch.

Self-Repair Loop

Build and tune the automated repair loop that pipes compiler, lint, build, and runtime errors back to the model with retry budgets and model escalation.

This loop is the primary quality lever - the difference between 60-70% and 90%+ build success rates.

Context Management

Build file-relevance retrieval so the agent sees the right files, not the whole codebase: dependency graphs, AST/tree-sitter-based chunking, embeddings, recency signals, and hybrid retrieval.

Implement conversation summarisation and memory for long sessions, and address long-project degradation through codebase summaries and periodic consistency passes.

Own token budgeting and prompt caching strategy.

Prompt Engineering as a Discipline

Own the system prompt and per-task prompt variants (new feature, bug fix, styling change).

Maintain few-shot examples and enforce coding conventions, stack rules, and prohibited behaviours such as no hardcoded secrets and no whole-file rewrites.

Version prompts like code with changelogs and rollback capability.

Evaluation and Quality Measurement

Design and own the evaluation suite: representative test prompts run on every prompt and model change, scored on build success rate, instruction adherence, and output quality including LLM-as-judge and visual/screenshot checks where relevant.

Define regression gates that block quality-degrading changes from shipping.

Treat evals the way engineers treat automated testing: versioned, automated, and tracked over time.

This responsibility is non-negotiable at this level.

Model Strategy and Cost

Design model routing - cheap and fast models for classification and small edits, frontier models for complex generation.

Drive cost optimisation through prompt caching, diff-based edits over full-file rewrites, and tighter context selection.

Track cost per agent run and tokens per task; evaluate new model releases against the eval suite and lead migrations when results justify it.

Safety and Reliability of Agent Behaviour

Defend against prompt injection from user content and fetched web content.

Ensure secrets never appear in generated client code.

Define what the agent's tools may and may not do in collaboration with the platform team.

Contribute to output moderation and abuse-pattern awareness.

Mentorship and Engineering Standards

Run code reviews, define engineering conventions for AI work, and raise the engineering bar across the AI team.

Work closely with the Senior MLOps Engineer on handoff of eval design, prompt configurations, and model routing logic.

Requirements:

Hands-on Production Ownership of LLM-Powered Systems with Agent Architectures (Mandatory)

Must have personally shipped and operated at least one complex production AI system - agentic, multi-step, or code generation - with end-to-end ownership of architecture, evaluation, and cost.

POCs, internal demos, and tutorial-grade work do not qualify.

5+ Years of Professional Software or AI Engineering Experience

With at least 3 years focused on LLM applications, AI engineering, or production AI systems.

Candidates with strong backend backgrounds and a clear, substantive pivot into LLM systems qualify.

Strong Python Proficiency and Service Development

Production-grade Python with FastAPI or equivalent: type hints, async patterns, streaming responses, testing, and packaging.

Not notebook-only.

Depth Across LLM APIs and Agent Systems

Production experience with at least two of OpenAI, Anthropic Claude, Google Gemini, or open-weight models (vLLM, Ollama, Together).

Production experience with at least one agent framework (LangGraph, CrewAI, AutoGen, LlamaIndex Agents) or hand-rolled equivalent.

Hands-on with tool calling, structured outputs, and multi-step reasoning.

Demonstrated, Systematic Evaluation Practice - Non-Negotiable

Must have built evaluation harnesses that gate production releases, not ad-hoc testing.

Hands-on with at least one of LangSmith, Langfuse, Promptfoo, Ragas, or DeepEval.

Candidates with no systematic answer to evaluation should not be considered at senior level regardless of other strengths.

Cost Discipline for Production AI

Track record of measurable cost optimisation on production AI features.

Able to speak in specifics: cost per request, savings achieved through caching or model routing, context reduction decisions.

AWS Working Knowledge

Hands-on with EC2, S3, IAM, and Docker.

Comfort with CI/CD workflows and deploying AI services.

Awareness of LLM Security Failure Modes

Familiar with prompt injection patterns, understands that system prompt rules alone are insufficient, and has experience with output validation and content safety in production.

Nice to Have

• Experience with AST/tree-sitter tooling, diff-based editing systems, or compiler-adjacent work
• MCP server authoring
• Open-source AI contributions
• Published technical writing on LLM systems
• Multi-modal model experience
• Fine-tuning exposure (LoRA, QLoRA, PEFT)

We’re on the hunt for a Principal Engineer who loves solving tough problems, mentoring others, and shaping the future of our platform. In this role, you’ll be leading the design and build of scalable systems and integrations across major cybersecurity platforms. Sometimes you’ll be deep in the code, other times you’ll be guiding teams and customers to the right solutions. If you enjoy balancing hands-on work with big-picture thinking, this could be your spot. 

About Us

At Metron Security, we help top cybersecurity companies supercharge their tools through automation and integrations. Our engineers connect and extend platforms like Splunk, IBM QRadar, ServiceNow, CrowdStrike, Cybereason, and many more. We believe in a developer-first culture where creativity, ownership, and continuous learning drive everything we do. 

Why You’ll Love Working Here

• A true developer-first environment where your ideas and technical chops matter.
• Hands-on exposure to 250+ security platforms (yep, really).
• Direct contact with customers so you can see the impact of your work right away.
• A fast-paced, growth-focused culture—but we also respect work-life balance. No weekends, and only occasional evening calls. 

What We’re Looking For 

We’re hoping to meet someone who has both deep technical expertise and natural leadership instincts. You think holistically about systems, enjoy digging into tricky problems, and can guide both teammates and customers to success.

Must-Have Skills

• Solid programming experience across multiple languages (Python, TypeScript, Java, Node.js, Angular, React, C#, C++… we’re language-agnostic and use the best tool for the job).
• Quick at learning new security platforms.
• Proven ability to design and build scalable systems, APIs, and integrations.
• Experience mentoring and leading engineering teams.
• Strong debugging and problem-solving skills in complex environments.
• Organized, reliable, and able to set and meet clear timelines.
• Comfortable working directly with customers to understand needs and design solutions.
• Familiar with cloud platforms (AWS, GCP, or Azure) and security best practices. 

Bonus Points If You

• Have experience building or leading integrations with enterprise security tools.
• Like approaching challenges with a “hacker mindset.” 
• Know your way around Docker, Kubernetes, and cloud deployments. 
• Contribute to open source or share technical insights publicly. 

What You’ll Do

• Be the face of Metron Security with our customers—collaborating on solutions and keeping communication clear.
• Bridge the gap between customers and our dev team, ensuring the right info flows both ways. 
• Mentor and train junior developers, helping them level up. 
• Step in to tackle tough technical problems when the team needs backup.
• Build and document knowledge about security platforms.
• Spot potential roadblocks early and help keep projects on track.

Who You Are

• Strategic thinker who isn’t afraid to roll up their sleeves.
• Clear communicator who collaborates openly.
• Proud of building strong, maintainable solutions that exceed expectations.
• Curious, quick learner, and always exploring new technologies.
• Positive, “let’s figure it out” teammate who lifts others up. 

At Metron Security, we’re all about helping security teams work smarter. If you’re excited to take on big engineering challenges, mentor others, and drive technical vision in a growing company, we’d love to talk.

About the Role

We are looking for a hands-on Applied AI / Full Stack Engineer to build AI-powered products and experiences. The ideal candidate should be comfortable working across AI, backend, and frontend and taking features from idea to production.

Key Responsibilities

• Build and deploy AI/LLM-powered applications and features.
• Develop AI agents, RAG pipelines, tool/function-calling workflows and integrations.
• Build scalable backend APIs and services.
• Develop frontend applications using React/Next.js.
• Integrate LLMs such as OpenAI, Claude, Gemini, etc.
• Work with databases, cloud platforms and production deployments.
• Collaborate with product and design teams and take ownership of features end-to-end.

Must-Have Skills

• 3–6 years of software engineering experience.
• Strong Python and/or TypeScript/Node.js.
• Strong React.js / Next.js / TypeScript experience.
• Hands-on experience with LLMs / Generative AI.
• Experience with RAG, AI Agents or tool/function calling.
• Experience building and deploying real-world products.
• Good understanding of APIs, databases and cloud deployment.

Good to Have

• LangChain / LangGraph / LlamaIndex
• PostgreSQL / Vector Databases
• AWS / GCP / Azure / Vercel
• Docker / CI/CD
• Experience in an early-stage startup or AI product company.

We are looking for builders who can take a problem, experiment, build, ship and improve it—not just candidates with AI keywords on their resume.

Job Description:

We are looking for a hands-on AI Engineer with experience in Generative AI and Agentic AI to build and deploy production-ready AI solutions.

Key Responsibilities:

• Develop and deploy GenAI and Agentic AI applications.
• Build RAG pipelines, LLM workflows, and AI agents.
• Develop solutions using Python, LangChain, LangGraph, LlamaIndex, or similar frameworks.
• Implement tool calling, context retrieval, and LLM orchestration.
• Integrate AI solutions with APIs and cloud platforms.
• Work with AWS/Azure/GCP, Docker, and CI/CD.

Required Skills:

• Strong Python programming skills.
• 3+ years of GenAI/Agentic AI experience.
• RAG and LLM orchestration.
• LangChain / LangGraph / LlamaIndex / AutoGen / CrewAI / Semantic Kernel.
• MCP and A2A knowledge.
• Cloud, APIs, Docker, and CI/CD experience.

Preferred Experience:

Hands-on experience building and deploying production-ready AI solutions.

About the Role

We are looking for an experienced AWS DevOps Engineer with around 4 years of hands-on experience to join our infrastructure/DevOps team. The ideal candidate will independently design, deploy, and maintain cloud infrastructure primarily on AWS, drive automation initiatives, mentor junior engineers, and work closely with cross-functional teams to build scalable, secure, and highly available systems. Exposure to Azure is a strong plus.

Key Responsibilities

·      Design, deploy, and maintain robust, scalable, and secure infrastructure on AWS

·      Architect and manage core AWS services such as EC2, S3, VPC, IAM, RDS, Lambda, ECS/EKS, Route 53, and CloudFront

·      Build, own, and optimize CI/CD pipelines (e.g., CodePipeline, Jenkins, GitLab CI, GitHub Actions) to enable fast and reliable deployments

·      Design and implement Infrastructure as Code (IaC) using Terraform / AWS CloudFormation

·      Set up and manage monitoring, logging, and alerting solutions (CloudWatch, ELK, Prometheus, Grafana, Datadog, etc.)

·      Implement and enforce security best practices including IAM policies, security groups, NACLs, KMS, Secrets Manager, and compliance standards

·      Lead troubleshooting and root cause analysis for infrastructure, deployment, and production incidents

·      Drive backup, disaster recovery, high-availability, and cost-optimization strategies (Reserved Instances, Savings Plans, right-sizing)

·      Containerize applications and manage orchestration using Docker, ECS, and/or Kubernetes (EKS)

·      Automate repetitive operational tasks through scripting and tooling

·      Support any hybrid or multi-cloud initiatives involving Azure services, where applicable

·      Mentor junior engineers and review their work, providing technical guidance

·      Collaborate with development, QA, security, and product teams to support and streamline application deployments

·      Maintain comprehensive documentation of architecture, configurations, processes, and runbooks

·      Participate in on-call rotations and incident response as needed

Required Skills & Qualifications

·      Bachelor's degree in Computer Science, IT, or a related field (or equivalent practical experience)

·      4+ years of hands-on experience working with AWS cloud services in a production environment

·      Strong expertise in core AWS services: EC2, S3, VPC, IAM, RDS, Lambda, CloudWatch, ECS/EKS, Route 53, ELB/ALB, Auto Scaling

·      Solid understanding of networking concepts (subnets, routing, security groups, load balancers, VPNs, VPC peering, Direct Connect)

·      Strong scripting/programming skills in Python, Bash, or PowerShell for automation

·      Hands-on experience with Infrastructure as Code tools such as Terraform or AWS CloudFormation

·      Proven experience with Linux and/or Windows server administration

·      Strong understanding of CI/CD pipelines, Git-based version control, and branching strategies

·      Solid experience with containerization and orchestration (Docker, ECS, or EKS/Kubernetes)

·      Experience with configuration management tools (Ansible, Chef, or Puppet) is a plus

·      Application Server Management — strong knowledge of networking, firewalls, load balancers, Nginx, Apache, etc.

·      Ability to independently read, interpret AWS documentation, and troubleshoot complex issues

·      Experience with cost optimization, security audits, and compliance frameworks (e.g., ISO, SOC2) is a plus

·      AWS certification (Solutions Architect Associate/Professional, DevOps Engineer Professional) preferred

Good to Have

·      Working knowledge of Microsoft Azure services (Virtual Machines, VNets, Azure DevOps, Azure Storage, Azure AD/Entra ID, AKS)

·      Experience with multi-cloud or hybrid-cloud environments

·      Familiarity with Azure Resource Manager (ARM) templates or Bicep

·      Any Azure certification (AZ-104, AZ-400, etc.)

Soft Skills

·      Strong analytical, problem-solving, and decision-making ability

·      Excellent verbal and written communication skills

·      Ability to mentor and guide junior team members

·      Proactive, ownership-driven approach to infrastructure and incident management

·      Strong collaboration skills in a cross-functional, team-oriented environment

·      High attention to detail with a focus on reliability and scalability

The role

A working product and a working deployment are two different things. You are the person who closes that gap.

You sit inside the client's head office. You get the deployment live, you get their teams using the dashboards, and you own whether the AI is returning something worth acting on. Every client is different: different languages on the floor, different store noise, different vocabulary for the same product, different CRM, different idea of what a good conversation looks like. The core platform does not change for each of them. You are the layer that makes it fit, and you are the one the client meets.

You are encouraged to spend time in stores. The engineers who do the best work here are the ones who have stood on a shop floor and watched where the pitch and the pipeline actually break. Nobody will make you go. You will also spend real time in the codebase, because you fix what you find rather than filing it.

What you build has a commercial edge to it. A pilot converts when the client sees the result they were promised, and an account grows when a second team inside it sees what is already sitting in their data. Both of those outcomes are yours to deliver, not somebody else's to chase.

How you will work

You design the deployment, you build it, and you own whether it holds up on a Saturday evening in a crowded store. Nobody hands you the plan, and nobody hands you the spec. You write both.

The decisions are yours. Which integration is worth the week, which vertical taxonomy needs building, what ships in the pilot and what waits, and when to tell a client that the thing they are asking for is the wrong thing to build. You go and find out what a client needs before anyone writes a line of code.

You will not be doing it alone. There are founders, AI engineers and product people around you, and they will build alongside you. What nobody will do is tell you what the client needs. That call is yours.

The work compounds if you do it well. What you learn on one deployment becomes a specification, then code, then a pattern the next one starts from. A year in, the deployments you designed should be running without you, and a new client should take a fraction of the time the first one did.

What you will do

Own the deployment end to end. Device provisioning, store connectivity, data flowing, first insight in front of the client. Get from kickoff to something real inside

the pilot window, and know by the halfway mark whether it is in trouble.

Get their HQ using it. A dashboard nobody opens is a failed deployment. Sit with the sales, marketing and L&D teams, show them what is in their own data, and

make sure the people who asked for this are actually looking at it every week.

Make the AI work on their floor. Their languages, their store noise, their product vocabulary. Benchmark transcription and speaker separation on their actual

audio, and fix what fails instead of explaining it away.

Build the vertical. Intent taxonomies, objection maps and prompt libraries for the category you are deployed into. A jewellery floor and an electronics floor do not

share a conversation model.

Wire it into their systems. CRM and POS integrations, so conversation data connects to what actually got sold and the insight can be checked against reality.

Build what the client asks for. Custom reports, dashboards and agents. Ground everything in source conversations and verify it before it ships, because a confident

wrong number costs an account.

Close the pilot. A pilot converts on results, not on effort. Know what the client agreed to judge this on, work backwards from it, and make sure the output in front of

their leadership at the end is the thing they asked for.

Grow the account. The same intelligence is worth something to marketing, L&D and category teams inside the same client. Spot which of them would benefit, show them what is already in their data, and hand a real opening to the account team.

Push it back into the product. Turn one-off client work into something the platform does by default, so the next deployment starts further ahead than this one did.

What we are looking for

Must have

• 0 to 5 years of experience. A consulting internship or an analyst role is the closest match to what this job actually asks for, but we care more about what you can do than where you did it
• Coding ability, ideally Python. Degree, internship, first job or your own projects. What we want to see is something you built that other people actually used
• Excel or Sheets at a real working level. A lot of the first conversation with a client happens in a spreadsheet before it ever happens in a dashboard
• The ability to explain a complicated idea simply. You will be taking AI output to people who do not think about models, and the explanation matters as much as the result
• Comfort at the boundaries. APIs, data pipelines, some frontend, some hardware when a device misbehaves
• An eye for where a deployment turns into more business, and the willingness to raise it yourself
• Heavy hands-on LLM usage. Prompts, evaluations, retrieval, and a clear view on where these tools break
• Fluent English and Hindi. A third Indian language counts for a lot, since the useful conversations happen on store floors and not only in HQ meeting rooms
• The instinct to go and find out what a client needs rather than waiting to be told

Good to have

Speech or audio work. Transcription, diarization, voice activity detection, or

anything that survives noisy real-world recording

Embedded or IoT experience, on ESP32 or similar

SQL and experience building things customers actually look at

Side projects, hackathons or internships where you shipped without a spec

and it worked

Click "Apply Now" in https://gosuperedtech.com/career/ai-system-engineer to apply

Role Overview

We are looking for a Junior AI System Engineer who is eager to build a career in AI systems, automation, backend workflows, cloud infrastructure, and intelligent product operations.

This role offers an opportunity to work closely with experienced engineers, product teams, and AI specialists on real AI-powered systems that support learners, educators, schools, and internal business operations.

At GoSuper EdTech, our cloud infrastructure is built on Google Cloud Platform — GCP. You will get hands-on exposure to GCP-based systems, backend services, AI integrations, deployment workflows, monitoring, cloud storage, databases, and automation pipelines.

You will help design, integrate, test, monitor, and maintain AI-enabled systems using modern tools such as AI APIs, LLMs, automation workflows, backend services, databases, GCP services, cloud deployment tools, and monitoring systems.

This role is ideal if you are curious about AI, comfortable with technical problem-solving, and interested in building reliable systems that connect software, data, cloud infrastructure, automation, and intelligent workflows.

What You’ll Do

• Support the development and maintenance of AI-powered systems, tools, and workflows.
• Assist in integrating AI APIs, LLM platforms, automation tools, and backend services into GoSuper products.
• Work with OpenAI, Gemini, Claude, or similar AI platforms under the guidance of senior engineers.
• Support AI and backend workflows deployed on Google Cloud Platform — GCP.
• Assist with GCP-based services such as Cloud Run, Compute Engine, Cloud Functions, Cloud Storage, Firebase, Firestore, Cloud SQL, BigQuery, Pub/Sub, Cloud Logging, and Cloud Monitoring, based on project needs.
• Help build AI workflows for content generation, chatbot systems, smart recommendations, internal automation, and productivity tools.
• Support backend integrations using Node.js, Python, REST APIs, webhooks, and third-party services.
• Assist in designing and maintaining system workflows that connect databases, applications, AI models, cloud services, and business tools.
• Work with databases such as PostgreSQL, MongoDB, Firebase, Firestore, Supabase, or similar platforms.
• Help test AI outputs, validate workflows, debug issues, and improve system reliability.
• Monitor system performance, API usage, errors, logs, workflow failures, and cloud service health.
• Support deployment, configuration, and maintenance of AI-enabled product features on GCP.
• Collaborate with product managers, developers, designers, QA teams, and business teams to understand requirements and deliver working solutions.
• Participate in daily standups, sprint planning, technical discussions, and team meetings.
• Document AI workflows, system logic, API integrations, prompts, GCP configurations, deployment steps, and troubleshooting processes.
• Continuously learn and apply best practices in AI systems, backend engineering, automation, GCP cloud infrastructure, and production support.

What We’re Looking For

• 6 months to 1 year of experience in AI systems, backend development, software engineering, automation, DevOps support, cloud support, system integration, or relevant internship/project experience.
• Basic understanding of AI tools, LLMs, APIs, automation workflows, and software systems.
• Working knowledge of JavaScript, TypeScript, or Python.
• Basic backend development experience with Node.js, Express, NestJS, FastAPI, or similar frameworks.
• Basic understanding of Google Cloud Platform — GCP or willingness to learn GCP-based deployment and monitoring workflows.
• Understanding of REST APIs, webhooks, third-party integrations, and data flow between systems.
• Interest in AI APIs, prompt workflows, chatbot systems, automation tools, and intelligent product features.
• Basic understanding of databases such as PostgreSQL, MongoDB, Firebase, Firestore, Supabase, or Redis.
• Ability to debug technical issues across APIs, workflows, logs, backend services, and cloud deployments.
• Good analytical thinking and problem-solving ability.
• Ability to write clear documentation for workflows, integrations, cloud configurations, and technical processes.
• Eagerness to learn new tools, AI platforms, system design concepts, GCP services, and cloud technologies.
• Good communication skills to work with technical and non-technical teams.
• Ownership mindset and willingness to take responsibility for assigned tasks.
• Comfortable working in a fast-paced startup environment.

Nice to Have

• Familiarity with AI APIs such as OpenAI, Gemini, Claude, or similar platforms.
• Basic understanding of prompt engineering and LLM-based workflows.
• Exposure to LangChain, LlamaIndex, embeddings, vector databases, or retrieval-augmented generation.
• Basic experience with GCP services such as Cloud Run, Cloud Functions, Firebase, Firestore, Cloud Storage, Cloud SQL, BigQuery, Pub/Sub, Cloud Logging, or Cloud Monitoring.
• Exposure to Google AI tools, Vertex AI, Gemini API, or AI-related services on GCP.
• Experience with automation tools, workflow builders, webhooks, or integration platforms.
• Exposure to Docker, CI/CD pipelines, GitHub Actions, deployment workflows, or cloud-based release processes.
• Experience working with logs, monitoring tools, API testing tools, or debugging platforms.
• Familiarity with Postman, Git, GitHub, Notion, Zoho, Slack, or similar productivity tools.
• Experience building chatbots, AI assistants, internal tools, or automated workflows.
• Personal, academic, internship, or open-source projects related to AI, automation, backend systems, GCP, or cloud tools.
• Interest in SaaS, EdTech, AI-powered products, and startup environments.

What You’ll Gain

• Hands-on experience building AI-powered systems in a real startup environment.
• Practical exposure to AI APIs, LLM workflows, automation systems, backend services, and GCP cloud infrastructure.
• Mentorship from senior engineers and product leaders.
• Experience working across AI, backend engineering, databases, APIs, integrations, deployment, system monitoring, and cloud operations.
• Opportunity to contribute to real product features used by learners, educators, schools, and institutions.
• Exposure to SaaS product development, EdTech workflows, AI-driven business solutions, and GCP-based production systems.
• Learning culture that encourages experimentation, feedback, and continuous improvement.
• Opportunity to understand how AI systems are designed, deployed, monitored, scaled, and improved in production.
• Access to Cult Elite and Cult Play Pass, offering wellness and lifestyle benefits to keep you energized and inspired.

Compensation

• Competitive salary with performance-based bonuses.
• Equity ownership through ESOPs — own a piece of the company you help build.
• Flexible remote work options with occasional Bengaluru office meetups.
• Health and wellness perks, including Cult Elite membership and Cult Play Pass for employees.
• Learning and development support to help you grow in AI systems, backend engineering, automation, SaaS, and GCP cloud technologies.
• Team retreats, virtual hangouts, and a collaborative work culture.

We are looking for a AI System Engineer who is eager to build a career in AI systems, automation, backend workflows, cloud infrastructure, and intelligent product operations. Apply in https://gosuperedtech.com/career/ai-system-engineer

Senior QA Engineer

Make quality part of the engineering system.

AbleCredit builds software for complex enterprise workflows where AI, APIs, business rules, human decisions, and real-world operations have to work together reliably. We care about building products that work in production - not just in demos. We're looking for a senior quality engineer who can move quality upstream: from release-time testing to better automation, contracts, observability, and engineering practices.

What You'll Own?

• Own quality strategy across web, mobile, backend APIs, integrations, and end-to-end workflows.

• Design and maintain automated regression suites for critical customer journeys.

• Build API, integration, contract, and workflow tests that catch failures before production.

• Partner with engineering and product teams during design - not only after development is complete.

• Define release readiness, risk-based testing, and production validation practices.

• Investigate escaped defects, identify systemic causes, and drive preventive improvements.

• Improve test data, environments, tooling, and CI integration so teams can ship confidently.

What We're Looking For?

• 5+ years in software quality engineering or test automation.

• Strong API and backend testing experience, including asynchronous and integration-heavy systems.

• Experience testing mobile and web applications and understanding client/ server failure modes.

• Ability to write automation in JavaScript/ TypeScript, Python, Java, or a similar language.

• Strong debugging skills across logs, network requests, databases, and distributed services.

• Experience with CI/CD and integrating automated tests into release pipelines.

• A product mindset: prioritize risk and customer impact rather than maximizing test-case counts.

Nice to Have

• Performance, load, security, or reliability testing.

• Experience with Playwright, Cypress, Appium, Postman/ Newman, k6, or similar tooling.

• Experience with event-driven systems, queues, webhooks, and long running workflows.

• Experience testing AI-assisted or non-deterministic product behavior.

How We Think About Quality?

Quality is an engineering responsibility. Automation should create confidence, not dashboards. A production escape should improve the system that allowed it to happen. The goal is simple: ship quickly without making customers our test environment.

This is a backend role. You won't build screens, and you don't need frontend experience. The mobile team will add a language picker and pass a locale to the backend. Everything behind that is yours: the data model, content pipelines, LLM generation, retrieval, audio, notifications, and making sure all of it holds up in production.

What you'll build

1. The language data model

• Design how language lives in the database: user language preference, per-story translations, fallback chains (e.g. pt-BR → pt → en), and versioning so a translation is marked stale when its English source changes.
• stories.translations (jsonb) already exists and nothing reads it yet. Decide whether it stays, or whether we move to a dedicated story_translations table, and write down why.
• Everything ships as new, reversible migrations. We never edit an existing migration.

2. The content translation pipeline

• Our library has already been translated into several languages using the Anthropic Batch API, with a two-pass generate-then-review process. Move this into the repo so it's idempotent, re-runnable and cheap, and so it handles only the stories that changed.
• Build a glossary and style layer: Hebrew terms, names of sages and sources, and terms that must never be translated. Add automated QA checks (completeness, glossary adherence, length drift, broken formatting) plus a sampling workflow for native-speaker review.

3. Generation in the user's language

• Reflections, bridge text, the three practices (Echo, Naming, Walking) and Path arcs are generated by Claude through shared prompt modules in our Supabase edge functions. Make them produce native, natural output in the target language. That means writing in the language directly, not translating English after the fact. Our existing rules must still hold, e.g. each practice carries a Hebrew term with its meaning explained, now explained in the user's language.
• Build a per-language evaluation harness so we can check quality before a language goes live and catch regressions when prompts change.

4. Multilingual matching

• Today, language-validation detects the language of the user's input and blocks anything that isn't English. Replace that gate with detection and routing.
• Story matching uses OpenAI text-embedding-3-large over pgvector. Measure how well non-English input retrieves the right English-indexed stories. Then decide between cross-lingual matching, per-language embeddings, or a hybrid, and back the decision with numbers.

5. Audio

• Stories and reflections are read aloud by ElevenLabs voices. Audio is currently stored per voice (audio_urls), so it has to become per voice and per language. Pick voices for each language, and plan batch pre-rendering, storage, cost and backfill.

6. Server-side copy

• Move push notification copy (including our Shabbat-aware scheduling), transactional and lifecycle emails, and database-driven home-screen messages out of the code and into a locale-aware string system with proper plurals and date formats.

7. Safe rollout

• Several app versions are live at the same time, and older builds can't be changed. Every change you make must stay backward compatible: English stays the default, current RPC signatures stay the same, and each language can be switched on independently behind a flag.
• Track cost and quality for each language: tokens, TTS credits, fallback rate and generation failures.

Our stack

• Backend: Supabase: Postgres (RLS, RPCs, pgvector, jsonb, pg_cron) and 50+ Deno/TypeScript edge functions
• AI: Anthropic Claude (Messages and Batch APIs, prompt caching), OpenAI embeddings, ElevenLabs TTS
• Data/scripts: Python and Node
• Other: RevenueCat, Resend, Expo Push/FCM. The app is Expo/React Native, but you won't need to work in it.

You'll be a fit if you have

• 5+ years of backend engineering, with strong PostgreSQL: schema design, migrations on live data, RLS, stored functions, and performance tuning.
• Production TypeScript (Deno or Node) and solid Python for data pipelines.
• Shipped LLM features to production, beyond prototypes: prompt design, structured output, batch processing, cost control, and above all evaluation. You know how to tell whether output in a language you don't speak is good.
• Built backend internationalization before: locale negotiation, fallback chains, ICU/CLDR plurals and dates, and translation workflows with versioning.
• Worked with embeddings and vector search, and can design a retrieval evaluation.
• Care about keeping production running: backward compatibility, feature flags, and rollouts that can be undone.
• Write clearly. Decisions here get written down before they get built.

Nice to have

• Experience with ElevenLabs or other TTS pipelines.
• Supabase-specific experience.

We are looking for an experienced Software Engineer to join an AI engineering startup developing a document collection platform for accountants and professional services firms. 

Preference to candidates from Kerala, India.

The product eliminates the friction involved in gathering client files by automating document requests, centralising their collection, and organising incoming documents according to each organisation’s preferred folder structure.

The ideal candidate will be able to take ownership of work from start to finish, communicate clearly, and deliver high-quality solutions within tight timeframes.

What You’ll Work On

You’ll work with Python and Django daily, including models, views, templates, background jobs, and the wider product around them.

The frontend uses Django templates with HTMX and Alpine.js, built with Vite, TypeScript, and Tailwind CSS. The stack runs in Docker using PostgreSQL, Redis, RabbitMQ, and Celery.

You may also assist with ancillary projects, including custom integrations.

Project-based training will be provided.

Technology Stack

Backend: Python, Django, PostgreSQL, Celery, Redis and RabbitMQ

Frontend: Django Templates, HTMX, Alpine.js, Vite, TypeScript and Tailwind CSS

Infrastructure: Docker

Must Have

• Strong Python and Django skills
• Comfortable working with Docker
• Fluent written and spoken English
• Clear communication skills, including providing concise updates, asking honest questions, and writing information that others can act on
• Evidence of exceptional ability—not simply a list of tools, but something challenging you have built or solved

Preference will be given to candidates with at least three years of relevant professional experience.

Nice to Have

• Frontend experience with HTML, CSS and JavaScript
• Experience with HTMX, Alpine.js, TypeScript or Tailwind CSS
• Knowledge of PostgreSQL, Celery or pytest
• Experience with integrations, including APIs, OAuth and cloud storage
• Basic accounting knowledge

How to Apply

Please do not send a generic CV alone. Your application must include:

1. Evidence of exceptional ability: Describe a project, open-source contribution, production system or challenging problem you solved. Include a link to the repository, write-up or demo where possible. Focus on your personal contribution by detailing the specific parts of the project where you played a critical role and explaining precisely what you built or solved.
2. What you accomplished: Provide a short explanation of the outcome in your own words.
3. The hardest part: Explain the hardest part of the problem and how you dealt with it.
4. Your use of AI: Explain whether you use AI in your work and, if so, how you use it.
5. Your professional experience and interests: Include a brief paragraph summarising your professional experience and general interests.

Applications that do not include the above Croissant details above will not be considered.

What We Offer

• For the right candidate, salary will not be a constraint
• Project-based training
• A rewarding career with genuine opportunities for professional growth
• The opportunity to work on an innovative AI-driven product
• A remote, full-time position
• 
  

Job Details and Application Submission

Location: Remote

Employment Type: Full-time

Contract: One-year contract, with the possibility of extension based on satisfactory performance

Probationary Period: Six months

Preferred Experience: Three or more years

Job Title: Platform Engineer

Location: Bangalore(Onsite)

Experience Level: 3-8

Salary Range: 20-30LPA

Description:

Join a team building an AI-native enterprise platform that helps businesses make faster, smarter and more consistent operational decisions using AI, enterprise data and workflow automation.

Design and build the core platform for enterprise decision workflows. Develop reusable workflow and decision runtimes. Build scalable, cloud-native distributed systems and event-driven architectures. Design enterprise-grade APIs and platform services. Build integrations with systems such as SAP and Oracle. Develop secure multi-tenant services with authentication and RBAC. Build and manage AWS cloud infrastructure and deployment systems. Implement monitoring and observability for production systems. Support both cloud and on-premise deployments. Enable faster onboarding and deployment of new enterprise workflows.

Requirements:

- Strong hands-on experience with Python

- FastAPI

- PostgreSQL

- Docker

- AWS

- Practical experience with Redis

- Kafka/event streaming

- REST APIs

- CI/CD

- Git

- Good understanding of Kubernetes

- Distributed systems

- Event-driven architecture

- Enterprise SaaS

- Microservices

- Strong backend engineering fundamentals

- Ability to design scalable, reliable and production-ready systems

Job Description:

Head of Engineering — Chennai (Onsite)About the Role

Job Details

Position: Head of Engineering

Department: Engineering

Experience: 6–8 Years

Employment Type: Full-time

Location: Chennai, On-site

Salary: Up to ₹24,00,000 per annum

About the Role

We’re looking for a Head of Engineering to take end-to-end ownership of engineering for a fast-moving product. You’ll be responsible for architecture, execution, product quality, engineering culture, and team growth.

This is a hands-on leadership role. You’ll spend approximately 60% of your time coding and reviewing code and 40% on product, people, and engineering leadership.

What You’ll Do

• Own engineering end to end, including architecture, development, delivery, quality, and hiring.
• Stay hands-on with the codebase, spending roughly 60% of your time writing and reviewing code.
• Establish and continuously improve the engineering workflow: how the team plans, builds, reviews, ships, and measures.
• Improve development velocity and reduce cycle time without compromising product quality.
• Drive AI-assisted software development across the engineering team using Claude Code and similar agentic coding tools as a core productivity lever.
• Establish practical systems and workflows that demonstrate measurable improvements in engineering throughput.
• Work closely with the founders on product strategy, technical trade-offs, priorities, and what to build next.
• Build, mentor, and scale a high-performing engineering team.

What We’re Looking For

• 6–8 years of professional software engineering experience.
• Experience taking at least one product from zero to launch.
• Experience building and scaling at least one product to a large user base.
• Strong hands-on expertise in Python and Node.js.
• Comfortable working with React Native / Expo.
• Strong understanding of PostgreSQL and database fundamentals.
• Previous experience leading a small engineering team.
• A leadership style based on ownership and technical example, rather than simply assigning tickets.
• Daily experience with agentic coding tools, with the ability to demonstrate how they have improved development speed and team throughput.
• Strong product instincts and the ability to form opinions about user problems, not just technical implementation.
• Based in Chennai or willing to relocate.

How We Work

We operate with high pace, high ownership, and short feedback loops.

You’ll be expected to get close to the product, understand the users, make decisions quickly, and ship within your first week.

If you enjoy building products from the ground up, staying close to the code, and using AI to fundamentally improve how engineering teams work, we’d love to hear from you.

How to Apply

Join Aura Gold and be part of building a high-performing team from the ground up!

Ability to commute/relocate:

• Chennai, Tamil Nadu (Chennai, Chennai District): Reliably commute or planning to relocate before starting work (Preferred)

Education:

• Bachelor's (Preferred)

Language:

• English, Tamil , Hindi (Required)

Location:

• Chennai, Tamil Nadu (Chennai, Chennai District) (Required)

Work Location: In person

Backend Developers

• Contract To Hire (Initial Engagement: 6 months)

Experience: 5+ years

Mandatory Skills:

● Node.js

● Python

● MongoDB

● PostgreSQL

● REST API design and development

● Backend architecture and service design

● Database design, indexing and query optimisation

● Performance tuning

● Authentication/authorisation

● Third-party integrations

● Asynchronous processing and background jobs

● Logging, monitoring and debugging

● Git and collaborative development

● Scalable, maintainable and testable backend services

● Architecture discussions, code reviews, debugging and production support

Good to have:

● Microservices

● Docker

● Cloud platforms

● Redis

● Message queues

● CI/CD

● Observability

Position Overview

We are seeking a versatile Senior Full Stack & AI Agent Developer to architect, build, and

maintain end-to-end software solutions spanning web platforms, desktop applications, and

autonomous AI agents capable of interacting with and controlling these software systems.

The ideal candidate will bridge traditional engineering software with cutting-edge artificial

intelligence to automate data processing and enhance operational decision-making. While

not strictly required, a background or strong interest in the energy sector—specifically

drilling and completion operations—is highly desirable.

Key Responsibilities

• Full Stack Development: Design, develop, and deploy robust web applications and

native desktop software utilized by engineering and operational teams.

• AI Agent Engineering: Build, train, and integrate autonomous AI agents and LLM-

driven workflows capable of interpreting data, executing commands, and safely

controlling desktop and web-based software.

• Workflow Automation: Translate complex workflows into intuitive software features

and autonomous agent actions, minimizing manual data entry and operational

bottlenecks.

• Data Integration: Handle high-frequency data streams and integrate them seamlessly

into user interfaces and backend AI models.

• Architecture & Scalability: Ensure high performance, security, and scalability across

cloud infrastructure (AWS/Azure), local desktop environments, and potential edge

computing setups.

• Cross-Functional Collaboration: Work closely with domain experts and end-users to

translate field challenges into technical product requirements.

Required Qualifications & Experience

• Experience: Minimum of 5 years of professional software development experience,

with a proven track record of delivering production-ready web and desktop

applications.

• Programming Languages: Strong proficiency in Python, JavaScript/TypeScript, and at

least one compiled language (C#, C++, or Java).• Web & Desktop Frameworks: Hands-on experience with modern frontend

frameworks (React, Angular, or Vue.js), Node.js, and desktop application development

(Electron, WPF, Qt, or Tauri).

• AI & Agent Tooling: Demonstrated experience building AI agents using LLM APIs

(OpenAI, Anthropic), open-source models (Hugging Face), LangChain, LlamaIndex,

AutoGPT, or custom agent architectures.

• Automation & UI Control: Expertise in software control mechanisms using tools like

Selenium, Playwright, PyAutoGUI, Appium, or computer vision-based GUI automation to

allow AI agents to navigate software.

• Cloud, DevOps & Databases: Experience with Git, Docker, CI/CD pipelines, cloud

platforms (AWS/Azure/GCP), RESTful APIs, GraphQL, and relational/NoSQL databases.

Preferred Qualifications (Strong Plus)

• Industry Domain Expertise: Prior hands-on development experience within the oil and

gas sector, specifically focused on drilling, completions, rig operations, or subsurface

engineering software.

• Data & Protocols: Familiarity with oilfield data standards (e.g., WITSML, OPC-UA) and

time-series databases.

• Experience deploying AI models and agents in edge or low-connectivity environments

(such as offshore rigs or remote drilling sites).

• Familiarity with safety-critical software design and cybersecurity standards in

industrial control systems (ICS/SCADA).

• Degree in Computer Science, Software Engineering, Petroleum Engineering, or a related technical discipline.

Insurity’s Next Data Scientist:

We are seeking a Data Scientist to join our Predict team, focused on building and maintaining predictive models that support underwriting, claims, and audit use cases across Workers' Compensation and Commercial Auto. This role will be based in India and will play a key part in scaling our data science capabilities.

What Our Data Scientist Will Do: 

• Develop predictive models using GLM and machine learning techniques such as GBM, Random Forest, and XGBoost
• Perform feature engineering, selection, and transformation to optimize model performance
• Analyze structured and unstructured datasets to uncover insights and support model development
• Indentify and integrate third-party data sources to augment existing datasets and improve model accuracy
• Collaborate with product and engineering teams to integrate models into production environments
• Use AWS tools such as SageMaker and EC2 to build, train, and deploy models
• Document modeling decisions and communicate findings to technical and non-technical stakeholders
• Support model monitoring and performance tracking over time
•  

Who We’re Looking For:

• 2-5 years of experience in data science or predictive modeling
• Strong understanding of GLM and ML algorithms (GBM, XGBoost, Random Forest)
• Experience with Python and relevant libraries (scikit-learn, pandas, NumPy)
• Familiarity with AWS tools, especially SageMaker and EC2
• Experience with feature engineering and model evaluation techniques
• Ability to translate business problems into analytical solutions
• Strong communication skills and ability to work collaboratively in a cross-functional team
• Bachelor's or Master's degree in a quantitative field (Statistics, Mathematics, Computer Science, Data Science)
• Active listening
• Analytical and critical thinking
• Self-starter and quick learner
• Detail-oriented
• Ability to collaborate and work independently 
• Written and oral English communication
• Time management including work planning, prioritization, and organization 
• Sound judgement
• Ability to handle multiple priorities or tasks
• Flexible and adaptable

Greetings from zealous services!

Job Title: Full Stack Developer PHP / Python & React.js

Location: Chennai, Tamil Nadu (On-site)

Shift: Rotational Shift

Experience: 1 - 4 Years

Employment Type: Full-Time

Salary: Competitive, based on experience

About the Role

We are looking for a skilled Full Stack Developer with experience in PHP and/or Python, along with modern front-end development using React.js, to join our development team.

The role involves building and maintaining scalable web applications, CRM platforms, dashboards, REST APIs, automation tools, and workflow-driven applications. The ideal candidate should have strong backend development skills and a good understanding of modern frontend technologies.

Key Responsibilities

• Design, develop, and maintain web applications using PHP (Core PHP, Laravel) and/or Python (Django, FastAPI).
• Develop scalable and high-performance RESTful APIs, microservices, and backend services.
• Build modern, reusable, responsive, and interactive user interfaces using React.js. • Work with HTML5, CSS3, JavaScript (ES6+), jQuery, AJAX, and Bootstrap 5. • Design, manage, and optimize databases using MySQL and/or PostgreSQL. • Implement authentication, authorization, and role-based access control (RBAC). • Integrate third-party APIs and internal services using REST/JSON. • Develop automation scripts, background tasks, scheduled jobs, and workflow automation.
• Debug, test, optimize, and maintain application performance and reliability. • Deploy and maintain applications on Linux servers and cloud platforms such as AWS and DigitalOcean.
• Work with Git, participate in code reviews, and follow Agile development practices. • Collaborate with developers and other team members to design and implement technical solutions.

Required Skills

Backend Development

• Strong hands-on experience with PHP and/or Python.
• PHP experience with Core PHP and Laravel.
• Python experience with Django, Django REST Framework, and/or FastAPI. • Strong understanding of REST API development and JSON.
• Experience with authentication, authorization, and API integration. • Strong knowledge of MySQL and/or PostgreSQL, including database design and query optimization.

Frontend Development

• Proficiency in React.js.
• Good knowledge of JavaScript (ES6+), HTML5, CSS3, jQuery, AJAX, and Bootstrap 5.
• Ability to develop responsive and reusable UI components.
• Familiarity with React components, hooks, and state management. Server & Development Tools
• Familiarity with Linux environments, cron jobs, and background workers. • Experience using Git and version control.
• Strong debugging, troubleshooting, analytical, and problem-solving skills. Nice-to-Have Skills
• Experience with Redux or Context API.
• Knowledge of JWT, OAuth, and API security.
• Experience with Celery, Redis, message queues, or background processing. • Exposure to CRM systems, dashboards, reporting tools, automation, or data pipelines.
• Familiarity with Docker, CI/CD pipelines, and microservices architecture. • Experience with AWS or DigitalOcean cloud deployment.
• Exposure to AI/ML integrations, analytics scripts, or automation platforms. • Understanding of application performance optimization and security.

Qualifications

• Bachelors degree in Computer Science, Information Technology, or a related field.
• 1 - 4 years of professional experience in Full Stack Development. • Candidates with strong experience in either PHP/Laravel or

Python/Django/FastAPI, along with frontend development skills, are encouraged to apply.

What We Offer

• Opportunity to work on real-world CRM, analytics, automation, and web application projects.
• Exposure to modern technologies including PHP, Laravel, Python, Django, FastAPI, React.js, REST APIs, and cloud platforms.
• Stable on-site rotational shift role with long-term career growth opportunities. • Collaborative and technically driven development environment.
• Opportunity to work on scalable applications and automation-driven platforms.

Role: Principal AI Architect — Multimodal Video Intelligence

Location: India Remote, with overlap with Singapore working hours

Employment Type: Full-time

Reporting to: Founder / CEO

Function: AI Architecture, Multimodal AI, Video Intelligence, Media Representation

About the Client

The client is building an AI-native media intelligence platform that transforms long-form video into structured, searchable, reusable and monetisable media intelligence.

The platform is not simply a video-clipping tool. We are developing a persistent intelligence layer for media, where video, audio, speech, text, objects, scenes, events, entities, emotions, narrative arcs and commercial signals are processed into a reusable representation that can support multiple downstream use cases, including:

• short-form clip generation;
• semantic search;
• scene and narrative understanding;
• contextual advertising;
• shoppable video;
• creator and content analytics;
• automated editing workflows;
• future media-intelligence APIs.

We are looking for a Principal AI Architect who can define and guide the AI architecture behind this platform.

Role Summary

The Principal AI Architect — Multimodal Video Intelligence will own the technical architecture for AI systems, including multimodal video understanding, persistent media representation, model orchestration, evaluation frameworks, and production AI design.

This is a hands-on architecture role. The ideal candidate can move between research papers, model selection, system design, data schemas, prototype review, engineering trade-offs, and implementation guidance.

You will work closely with the Founder / CEO, senior AI engineers, computer vision engineers, backend engineers and external vendors to convert the product and IP vision into a robust technical system.

Key Responsibilities

1. AI System Architecture

• Define the end-to-end AI architecture for long-form video understanding.
• Design the processing pipeline from video ingest to structured media intelligence.
• Define how vision, audio, speech, text, metadata and user signals should be fused.
• Design the architecture for reusable media intelligence rather than one-time clip generation.
• Ensure the system can support multiple downstream applications from the same processed media layer.

2. Persistent Media Representation

• Design persistent media representation layer across multiple levels, including frame, object, shot, scene, segment, entity, event and full-video levels.
• Define what intelligence must be stored permanently versus computed on demand.
• Design schemas for temporal, spatial, semantic, narrative and commercial metadata.
• Define provenance, confidence, model versioning and evidence-tracking requirements.
• Ensure the representation remains usable even when underlying AI models are replaced or upgraded.

3. Multimodal Model Strategy

• Select and evaluate appropriate models for video, image, audio, speech, OCR, entity extraction, scene understanding, action recognition, embeddings, reranking and LLM/VLM reasoning.
• Decide where to use open-source models, commercial APIs, fine-tuning or custom models.
• Define model interfaces so models can be swapped without breaking downstream systems.
• Guide model benchmarking for accuracy, latency, cost and scalability.
• Prevent over-dependence on any single model vendor or API.

4. Temporal and Narrative Intelligence

• Design approaches for understanding long-form video structure, including scenes, events, story arcs, character/entity continuity and engagement peaks.
• Define methods to identify clip-worthy moments across different content types.
• Support narrative scoring, highlight ranking, scene segmentation and coherence validation.
• Ensure that clips are not only visually interesting but contextually and narratively coherent.

5. Evaluation and Benchmarking

• Define objective evaluation frameworks for AI outputs.
• Build or guide creation of benchmark datasets and UAT criteria.
• Define metrics for clip quality, scene accuracy, entity continuity, timestamp alignment, hallucination control, ranking quality, retrieval precision and cost efficiency.
• Establish model and prompt evaluation processes.
• Create regression-testing methodology when models, prompts, schemas or scoring logic change.

6. Search, Retrieval and Knowledge Layer

• Design hybrid search architecture across transcript, visual events, metadata, embeddings and structured knowledge.
• Define when to use relational storage, vector databases, graph databases and object storage.
• Design queryable media intelligence for downstream APIs and applications.
• Support knowledge-graph or ontology-based representation where useful.
• Ensure retrieved outputs are evidence-backed and timestamp-grounded.

7. Production AI Architecture

• Work with AI engineers to convert architecture into deployable services.
• Guide decisions on batching, GPU inference, model serving, queues, retries, observability and cost controls.
• Review pipeline designs involving FFmpeg, GStreamer, DeepStream, TensorRT, Triton, ONNX, cloud services and model APIs.
• Define failure-handling, reprocessing, versioning and rollback mechanisms.
• Support scalable design without premature overengineering.

8. IP and Technical Differentiation

• Help translate AI architecture into defensible technical differentiation.
• Support patent-related technical disclosures where required.
• Identify what is proprietary versus commodity.
• Avoid building a generic wrapper over existing models.
• Ensure the architecture reinforces the core thesis of persistent, reusable media intelligence.

9. Team Guidance

• Provide technical direction to senior AI engineers and computer vision engineers.
• Review designs, experiments, evaluation results and architecture decisions.
• Mentor engineers without becoming a pure people manager.
• Help define technical milestones for the first 90, 180 and 365 days.
• Support hiring, technical interviews and vendor evaluation where needed.

Required Experience

The ideal candidate should have:

• 8+ years of AI/ML experience, with significant exposure to computer vision, video AI, multimodal AI, retrieval systems or production ML architecture.
• Strong experience designing AI systems, not only implementing isolated models.
• Hands-on experience with video understanding, temporal modelling, multimodal pipelines, VLMs, LLMs, embeddings, ranking or retrieval.
• Experience taking AI systems from prototype to production.
• Strong knowledge of Python and modern AI/ML frameworks such as PyTorch, TensorFlow, Hugging Face or equivalent.
• Experience with model evaluation, benchmarking, error analysis and dataset design.
• Understanding of production architecture: APIs, queues, databases, cloud, model serving, observability and deployment trade-offs.
• Ability to work with founders and engineers in a high-ambiguity startup environment.

Strongly Preferred Experience

• Video understanding, action recognition, scene segmentation, event detection or video retrieval.
• Multimodal AI involving video, audio, speech, text and metadata.
• LLM/VLM orchestration for structured outputs.
• Prompt/version management, schema validation and hallucination control.
• Embedding search, vector databases, reranking and retrieval evaluation.
• Knowledge graphs, ontologies, entity resolution or temporal knowledge representation.
• Model serving using TensorRT, Triton, ONNX, vLLM, DeepStream or similar.
• Experience with long-form video, OTT, sports media, entertainment, creator platforms, advertising technology or social commerce.
• Experience contributing to patents, technical disclosures or investor diligence.

Technical Areas

The candidate should be comfortable discussing and making architecture decisions across:

• Computer vision;
• video AI;
• multimodal fusion;
• speech-to-text;
• OCR;
• image/video embeddings;
• VLMs and LLMs;
• semantic search;
• vector databases;
• graph databases;
• temporal reasoning;
• ranking and scoring systems;
• prompt orchestration;
• model evaluation;
• model versioning;
• data lineage;
• GPU inference;
• cloud AI deployment.

What This Role Is Not

This is not a role for someone who has only built:

• chatbots;
• basic RAG demos;
• LangChain prototypes;
• prompt-engineering workflows;
• simple OpenAI/Gemini API wrappers;
• dashboards over model outputs;
• classical computer vision demos without production architecture;
• MLOps pipelines without AI system-design depth.

The role requires architectural depth in AI systems, not just familiarity with AI tools.

First 90-Day Expectations

First 30 Days

• Review product thesis, patent direction, prototype plans and existing technical assumptions.
• Assess current team capability and architecture gaps.
• Define the first version of AI architecture.
• Identify immediate technical risks and validation priorities.

First 60 Days

• Deliver a detailed architecture document covering media representation, model stack, pipeline design, storage strategy, evaluation framework and implementation roadmap.
• Define the canonical media-intelligence schema.
• Define model-selection and benchmarking criteria.
• Guide senior engineers on first implementation milestones.

First 90 Days

• Help the team implement and validate the first working version of the persistent media-intelligence layer.
• Establish evaluation datasets and UAT metrics.
• Review prototype outputs and improve architecture based on evidence.
• Produce a 6-month AI roadmap with technical risks, milestones and resourcing needs.

Success Metrics

The Principal AI Architect will be successful if:

• They have a clear AI architecture that the engineering team can execute.
• The platform does not collapse into a generic clip-generation pipeline.
• The media representation is reusable across multiple use cases.
• Models, prompts and schemas are versioned and testable.
• AI outputs are measurable through objective benchmarks.
• Snehashish, Abhishek and other engineers have clear technical direction.
• The architecture supports both product execution and investor/IP defensibility.

Candidate Personality Fit

The right candidate should be:

• intellectually strong but practical;
• hands-on enough to review code and experiments;
• comfortable with ambiguity;
• willing to challenge assumptions with evidence;
• able to simplify complex AI architecture for engineers and investors;
• disciplined about evaluation, cost and production constraints;
• not attached to one model, tool or vendor;
• able to work in a founder-led early-stage startup. 

Role Overview

We are looking for a GCP Data Engineer with 10+ years of experience to design, develop, and optimize scalable cloud-based data solutions. The ideal candidate will have strong hands-on expertise in GCP, BigQuery, and advanced SQL, with experience building data pipelines and working with large-scale datasets.

Key Responsibilities

• Design and develop scalable data pipelines and ETL/ELT processes on GCP.
• Build, optimize, and maintain data solutions using Google BigQuery.
• Develop complex SQL queries for data transformation, aggregation, and analysis.
• Design efficient data models and optimize pipelines for performance, scalability, and cost.
• Integrate data from multiple sources and ensure data quality, reliability, and availability.
• Troubleshoot pipeline and data issues and drive continuous improvement.
• Collaborate with data architects, analysts, application teams, and business stakeholders.
• Follow best practices for cloud security, data governance, testing, and documentation.

Required Skills

• 8+ years of Data Engineering experience
• Strong hands-on experience with GCP, Django, and MongoDB
• Extensive experience with BigQuery
• Advanced SQL skills
• Strong understanding of ETL/ELT and data pipeline development
• Data modeling and data warehousing experience
• Experience handling large-scale datasets and performance optimization
• Strong problem-solving and communication skills

Good to Have

• GCP services such as Cloud Storage, Dataflow, Pub/Sub, Cloud Composer, or Cloud Functions
• Python or other data engineering languages
• Experience with data governance and security
• Agile development experience

Required Skills:-

• 4+ years of experience in Software Testing (Manual & Automation).
• Strong experience with Selenium or Playwright.
• Hands-on experience in API Testing (Postman, REST Assured, Swagger, etc.).
• Experience with CI/CD pipelines (Jenkins, GitLab CI, Azure DevOps, GitHub Actions).
• Strong understanding of Functional, Regression, and Non-functional Testing.
• Excellent analytical and debugging skills.

AI-Specific Skills

• Hands-on experience in GenAI / AI Testing.
• Experience testing LLM-based applications.
• Strong understanding of prompt engineering and prompt validation.
• Knowledge of LLM behavior, model variability, and non-deterministic outputs.
• Experience validating AI outputs for accuracy, hallucinations, bias, and safety.
• Test data management for AI applications.
• Understanding of Responsible AI testing concepts.

Company Overview:

Planview is hiring a DevOps Engineer in Bengaluru, India to support Planview SaaS applications across the product line. You will work in a global, collaborative team — owning CI/CD pipelines, cloud infrastructure, and automation to keep deployments fast and systems reliable.

Responsibilities

• Build and maintain CI/CD pipelines in Jenkins for reliable, fast delivery.
• Manage containerized workloads on Docker and ECS — task definitions, services, and clusters.
• Provision and manage AWS infrastructure using Terraform (CloudFormation a plus).
• Automate configuration and deployment tasks using Python (Ansible a plus).
• Set up and maintain monitoring and alerting via New Relic (CloudWatch, Datadog, or Prometheus/Grafana a plus).
• Write Shell and Python scripts to automate operations and reduce manual work.
• Manage Git workflows — branching, merge strategies, and pull request reviews.
• Administer and support MSSQL databases underpinning the product line — backups, restores, and basic performance troubleshooting.
• Troubleshoot deployment, performance, and infrastructure issues with development teams.
• Participate in on-call rotations and drive incident response.
• Continuously improve infrastructure resilience and deployment speed.
• Apply AI-assisted engineering tools (e.g., GitHub Copilot, Claude Code) to speed up IaC authoring, pipeline debugging, and day-to-day scripting.

Qualifications

Must-Have Skills

• Experience: 4–6 years of experience in DevOps, SRE, or Infrastructure Engineering.
• OS: Linux & Windows administration (systemd, package management, log analysis).
• Cloud: AWS (Active Directory, ECS, EC2, CloudFront, S3, VPC, IAM, RDS, Lambda basics).
• Source Control: Git — branching, merge/rebase, PR reviews.
• CI/CD (Jenkins): Pipeline creation and basic Groovy scripting.
• Containerization (Docker + ECS): Task definitions, services, and clusters.
• IaC: Terraform.
• Monitoring: New Relic.
• Scripting: Bash and Python scripting for automation.
• Networking Basics: DNS, load balancers, security groups, VPNs.
• Logging: ELK stack / CloudWatch Logs.
• Database: MSSQL administration — backups, restores, basic performance troubleshooting.
• Infrastructure Automation: Hands-on experience automating infrastructure provisioning, configuration, and deployment end-to-end.
• AI-Assisted Engineering: Comfortable working with AI coding/DevOps assistants (e.g., GitHub Copilot, Claude Code) for IaC generation, scripting, and troubleshooting — verified via a mandatory AI proficiency assessment during interviews.

Nice-to-Have Skills

•     Configuration Management: Ansible.

•     Additional IaC: CloudFormation.

•     Architecture: Knowledge of microservices architecture.

•     Cloudflare: DNS, CDN, WAF.

•     Artifact Repositories: Nexus, JFrog Artifactory, ECR.

•     Other CI/CD Tools: GitHub Actions.

•     AWS cost optimization / FinOps awareness.

•     Datadog, CloudWatch, or Prometheus/Grafana.

•     AIOps: Exposure to AI-driven anomaly detection, root-cause analysis, or incident triage (e.g., Dynatrace Davis AI, Datadog Bits AI, Harness AIDA).

•     Database Basics: RDS backups, restores, performance tuning.

We are looking for a senior, hands-on DevOps and Backend Integration Engineer to lead the production deployment and integration of an existing application ecosystem.

The platform currently includes a Flutter mobile application, a Laravel backend and admin panel, Node.js/AdonisJS APIs, a Python recommendation service, Redis, MySQL, Nginx, and AWS S3.

This is not a greenfield development role. The primary objective is to audit the existing system, establish a reliable production infrastructure, integrate all services, migrate traffic safely, and complete the production launch.

Responsibilities

• Audit the existing Hostinger environment, source repositories, application dependencies, database, Redis configuration, and deployment process.

• Design a secure and maintainable production architecture for Laravel, Node.js/AdonisJS, Python, Redis, MySQL, Nginx, AWS S3, and the Flutter application.

• Provision and configure Linux production servers, runtimes, SSH access, environment variables, permissions, SSL, and basic server security.

• Deploy and configure the Laravel application, admin panel, APIs, scheduled tasks, queues, and database connectivity.

• Deploy the Node.js/AdonisJS services with a reliable build, startup, logging, and process-management setup.

• Build a Git-based CI/CD pipeline for staging and production, including secrets management, deployment validation, and basic rollback handling.

• Configure Nginx as a reverse proxy and route traffic between Laravel and Node.js services using API versions and endpoint rules.

• Install and integrate Redis for agreed caching, queue, or session-management requirements.

• Configure AWS S3, IAM permissions, secure file access, and photo-upload integration to replace local server storage.

• Integrate the existing Python recommendation service with the Node.js backend, including timeout, retry, error-handling, and service-health scenarios.

• Support controlled migration of API traffic from Laravel to Node.js while preserving existing API contracts.

• Verify Flutter API compatibility, production environment configuration, authentication flows, media uploads, and backend-related integration issues.

• Conduct end-to-end, regression, and smoke testing across Flutter, Nginx, Laravel, Node.js, Redis, Python, MySQL, and AWS S3.

• Perform production cutover, validation, troubleshooting, and technical handover.

• Deliver clear architecture, deployment, routing, environment, rollback, and operational documentation.

Required Experience

• 5+ years of professional backend, DevOps, infrastructure, or platform-engineering experience.

• Strong hands-on Linux server administration and production deployment experience.

• Proven experience deploying and operating Laravel/PHP and Node.js applications.

• Strong knowledge of Nginx reverse proxy configuration, SSL, upstream services, and API routing.

• Experience creating CI/CD pipelines using GitHub Actions, GitLab CI, Bitbucket Pipelines, or a comparable platform.

• Practical experience with AWS S3, IAM permissions, secure media uploads, and cloud-storage integration.

• Experience with Redis, MySQL, background workers, queues, scheduled jobs, and application caching.

• Experience integrating Python services or machine-learning/recommendation APIs with Node.js applications.

• Good understanding of REST APIs, API versioning, authentication, secrets management, logging, monitoring, backups, and rollback procedures.

• Ability to independently investigate an existing codebase and resolve production integration problems.

• Strong written English and the ability to produce clear technical documentation.

Nice to Have

• Experience with AdonisJS.

• Experience supporting Flutter applications and mobile backend integrations.

• Experience migrating applications from shared hosting or Hostinger to a production cloud server.

• Experience with Google Maps Platform or location-based application services.

• Docker experience is helpful, although Kubernetes is not required.

Expected Deliverables

• Documented production architecture.

• Fully configured production infrastructure.

• Working Laravel, Node.js/AdonisJS, Python, Redis, MySQL, Nginx, and AWS S3 integrations.

• Functional staging and production CI/CD workflows.

• Tested Laravel and Node.js coexistence with controlled API routing.

• Successful end-to-end production deployment.

• Rollback, deployment, configuration, and operational documentation.

Engagement Details

• Contract duration: approximately 4–5 weeks.

• Work arrangement: remote.

• Availability: candidates should be able to begin shortly and provide regular written progress updates.

• The current Node.js APIs and recommendation algorithm already exist. Major new product features, algorithm redesign, extensive Flutter feature development, and database redesign are outside the initial scope.

How to Apply

Please include:

1. Examples of Laravel and Node.js systems you have deployed to production.

2. Details of a CI/CD pipeline and Nginx routing setup you personally implemented.

3. Your experience integrating Redis, AWS S3, and Python services.

Job Title: Full Stack AI Engineer

Location: Remote/Hyderabad

Experience Level: 3-5

Salary Range: 12-18LPA

Application Link:https://beyond.ciltriq.com/apply/BUILD

Description:

Join a team building AI-powered systems that solve complex business problems and automate operational workflows across document processing, voice agents, enterprise integrations, workflow automation, and multi-agent systems.

Strong full-stack foundations: frontend state management, asynchronous user experiences and performance; backend API design, authentication, data modelling, databases, queues and distributed systems.

Strong coding ability in Python and JavaScript or TypeScript, with practical experience in modern frontend frameworks and backend services.

Requirements:

- Design and build complete systems: frontend applications, backend services, APIs, databases, data pipelines and integrations with customer systems.

- Build multi-agent workflows with clear agent responsibilities, tool access, shared state, context management, routing, handoffs and coordination across sequential and parallel tasks.

- Make agent execution dependable through durable state, checkpoints, retries, timeouts, idempotency, recovery and human approval or review where needed.

- Deliver document-processing pipelines, voice agents and retrieval-based AI applications, connecting model outputs to useful actions in real business workflows.

- Own quality in production: automated tests, AI evaluations, guardrails, observability, access controls, deployments, incident response and clear documentation.

- Choose where AI adds value and where deterministic software is the better fit. Balance accuracy, latency, cost, security and maintainability.

- Improve reusable engineering foundations, review code and help other engineers grow as the team expands.

- A solid understanding of tool calling, structured outputs, retrieval, context and memory management, model selection and evaluation.

- Practical cloud and deployment experience, including containers, CI/CD, secrets management, logging, monitoring and production debugging.

- Ability to reason from first principles, investigate failures across system boundaries and communicate technical decisions clearly to customers and teammates.

- Useful additional experience: Document AI and OCR, real-time voice systems, enterprise integrations, agent protocols such as MCP, and orchestration frameworks.

- Useful additional experience: Mentoring engineers or building reusable platforms.

About Us:

CLOUDSUFI, a Google Cloud Premier Partner, is a global leading provider of data-driven digital transformation across cloud-based enterprises. With a global presence and focus on Software & Platforms, Life sciences and Healthcare, Retail, CPG, financial services and supply chain, CLOUDSUFI is positioned to meet customers where they are in their data monetization journey.

Our Values

We are a passionate and empathetic team that prioritizes human values. Our purpose is to elevate the quality of lives for our family, customers, partners and the community.

Equal Opportunity Statement

CLOUDSUFI is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified candidates receive consideration for employment without regard to race, colour, religion, gender, gender identity or expression, sexual orientation and national origin status. We provide equal opportunities in employment, advancement, and all other areas of our workplace. Please explore more at https://www.cloudsufi.com/

Role :

A Software Engineer who builds the tools this company runs on. You build agent loops, and the loops build the solutions. You work towards a Company Brain that anyone here can ask.3–5 years’ experience · Reports to the CFO · 

THE KEY SKILL

You build the agent loops that build the solutions. You will not write every automation by hand. You build the loops that

write them. Ship a prototype every week. You ship something every day.

You’ll be building a Company Brain with access control. One system that holds what the company knows about finance,delivery and people. Anyone can ask it a question. Each person sees only what they are cleared to see.

One hard filter. If you cannot write and debug production code, and have not done it before, please do not apply.

CORE RESPONSIBILITIES

• Work the backlog: You pick items off a live, ranked backlog. You learn each function by building inside it. There is no discovery phase. What you learn goes back into the backlog and changes what comes next.

• Build the product: You design, build and ship tools that people use every day. Reconciliation, MIS, the deal desk,quote to cash, or whatever the real bottleneck turns out to be. You choose the tools and frameworks.

• Wire the data: Connect the systems each team already uses, so that the same number means the same thing everywhere.

• Make it visible: You build live dashboards and alerts that leaders read on their own, instead of asking someone for a report.

• Keep it running: You own uptime and accuracy for everything you build. Anything that touches money or people needs a person in the loop.

THE STACK

• Build with: Python and TypeScript. You write production code. Frontier model APIs from Anthropic, OpenAI or Google, with tool calling and structured output. At least one agent framework. MCP to connect agents to internal systems.Postgres and pgvector, or something similar, for retrieval. You deploy on GCP, and you debug your own work.

• Work in agents daily: Claude Code, Cursor or something like them, as the way you write code every day. You should have a clear view on how to run the loop, and on when a person has to step in.

• Connect to: The systems we already run on for accounting, CRM, hiring and IT support, along with Google Workspace.Most of the work is getting them to agree with each other.

• Check what you ship: Anything that produces a number needs a way to catch it going quietly wrong. Test sets, regression checks, and alerts on the output as well as on the job.

WHAT GOOD LOOKS LIKE

• Something you built is running by week two, and someone is using it.

• By day 90, time spent on reconciliation or reporting is down by a number you can defend to the CFO.

• Every tool you ship has a named owner who is still using it 60 days later. That is the measure that counts.

• Leaders stop asking for numbers, because they can already see them.

• By the end of your first year, a first version of the Company Brain answers real questions about Finance, and each

person who asks sees only what they are cleared to see.

WHO THIS IS FOR

• You have built products: 3 to 5 years at a software product company, on a product with real users at scale. That means 100k+ monthly active users, or heavy daily use by a large enterprise customer base. You have owned code in production, in front of real users, long after it shipped.

• You ship alone: You are comfortable as the only engineer in the room, and the only person on call for what you built.

• You work out new ground fast: A domain you do not know is interesting to you. You start without waiting for a spec or an expert.

• You are fluent with agents: One person cannot cover a whole company by hand. You use agent loops heavily and youare good at it.

• You write and speak clearly: Half this job is pulling a process out of a finance or delivery lead and giving it back to them correctly. You work remotely, so this matters a great deal.

HOW WE WILL ASSESS

• A design problem: Live. We give you a function of the B2B company, and you design the system for it. We watch how you break down a domain you do not know, how you size it, and what you leave out on purpose.

• A build exercise: Live and screen-shared, on your own setup, with your own agents. You build the way you normally build. We watch how you run the loop, when you step in, and what you decide to skip.

• Your work and your questions: We talk about what you have shipped before. You ask us whatever you want.

Communication is not a separate round. All three sessions are live, and how clearly you explain your thinking is part of how we judge you.

WHERE IT LEADS

You report to the CEO and CFO from your first day. Your charter covers the whole company. Nothing sits between you and production. Very few engineering jobs offer all three at once, and that is why this one exists.

In 18 months you will know how this company really runs: the data, the money, and the gaps between teams. The rolethen changes shape to fit whatever the biggest open problem is by then.

At Nineleaps, we work on bleeding-edge technology with class-leading engineering practices on products that touch the lives of millions of users. We endeavor on doing things the right way, while also promoting a culture of excellence.

About the Role:

We are looking for a Data Analyst with strong analytical and problem-solving skills to transform complex data into meaningful, actionable business insights. The role involves working with large datasets, conducting deep-dive analysis, driving automation, and supporting data-driven product and business decisions.

Key Responsibilities:

• Analyse historical and large datasets to understand data sources, identify trends and patterns, and uncover meaningful insights.
• Write complex SQL queries and leverage Python to perform data analysis, ad hoc investigations, and solve business problems.
• Create reports and translate analytical findings into clear, concise, and actionable recommendations for stakeholders.
• Identify opportunities to drive automation and process improvements, improving efficiency and reducing manual effort.
• Communicate data-driven insights effectively to both technical and non-technical stakeholders in a clear and impactful manner.
• Maintain accurate documentation, ensure high-quality deliverables, and consistently meet defined timelines.

Requirements:

• 3–6 years of experience in Data Analytics, Business Intelligence, Data Engineering, or a similar analytical role.
• Strong hands-on expertise in Python and advanced SQL, with the ability to work with and analyse large datasets.
• Experience working with Google Sheets, and implementing automation through data pipelines or workflows.
• Strong analytical and problem-solving skills, with the ability to interpret complex data and derive actionable insights.
• Excellent communication skills with the ability to effectively present methods, results, and recommendations to stakeholders.
• Ability to collaborate effectively with remote and geographically distributed teams across different time zones.

Company Link: https://www.nineleaps.com/

Company LinkedIn: https://www.linkedin.com/company/nineleaps/

Job Description: Senior Java/Python Developer (AI & GenAI Specialist)

Location

Position Summary

We are seeking an experienced Senior Java/Python Developer with strong expertise in enterprise application development and extensive hands-on experience in Artificial Intelligence (AI), Generative AI (GenAI), Large Language Models (LLMs), and AI-powered application development. The ideal candidate will lead the design, development, and deployment of scalable, intelligent solutions that integrate modern AI technologies with enterprise-grade Java and Python ecosystems.

This role requires a combination of strong software engineering skills, AI innovation capabilities, and architectural leadership.

Key Responsibilities

• Application Development

• Design, develop, and maintain scalable enterprise applications using Java and Python.

• Develop RESTful APIs, microservices, and event-driven architectures.

• Build high-performance backend systems using Spring Boot, FastAPI, Flask, or Django.

• Ensure code quality through unit testing, integration testing, and code reviews.

AI & Generative AI Development

• Design and implement AI-powered solutions leveraging Large Language Models (LLMs).

• Develop intelligent applications using OpenAI, Azure OpenAI, Anthropic Claude, Google Gemini, and similar platforms.

• Build Retrieval Augmented Generation (RAG) architectures for enterprise knowledge systems.

• Implement AI agents, copilots, chatbots, virtual assistants, and workflow automation solutions.

• Engineer prompts and build prompt orchestration frameworks.

• Develop multi-agent AI systems and autonomous AI workflows.

Required Technical Skills

Core Programming

• Expert-level proficiency in:

o Java (Java 11/17/21)

o Python 3.x

• Strong understanding of OOP, design patterns, and software engineering principles.

Java Technologies

• Spring Boot

• Spring Cloud

• Hibernate/JPA

• Microservices Architecture

• Kafka/RabbitMQ

• REST API Development

Python Technologies

• FastAPI

• Flask

• Django

• Pandas

• NumPy

• Async Programming

Generative AI & LLMs

• OpenAI APIs

• Azure OpenAI

• LangChain

• LangGraph

• LlamaIndex

• Semantic Kernel

• Hugging Face

• Prompt Engineering

• RAG Frameworks

• AI Agent Frameworks

• Vector Databases (Pinecone, Weaviate, ChromaDB, Milvus, FAISS)

Preferred Qualifications

• Experience developing enterprise AI copilots and intelligent assistants.

• Experience implementing AI solutions using Microsoft Copilot Studio, Azure AI Services, or similar platforms.

• Knowledge of AI governance, responsible AI, security, and compliance frameworks.

• Experience in travel, finance, telecom, retail, or large enterprise environments.

• Exposure to graph databases and knowledge graphs.

• Understanding of multimodal AI (text, image, audio, video).

Educational Qualifications

• Bachelor's or Master's degree in Computer Science, Information Technology, Artificial Intelligence, Data Science, or related discipline.

• Generative AI certifications preferred.

Key Competencies

• Solution Architecture

• AI Innovation & Thought Leadership

• Problem Solving

• Stakeholder Management

• Technical Mentoring

• Agile Development

• Analytical Thinking

• Communication & Presentation Skills

Success Metrics

• Delivery of scalable AI-enabled enterprise solutions.

• Reduction in operational effort through AI automation.

• Successful deployment of GenAI applications into production.

• Application performance, reliability, and security.

• Adoption of AI best practices across development teams.

Sr. Technology Architect

Experience Range: 12–15+ years of IT experience, including 3–5+ years in leadership / people management roles.

Location: Chennai, Hyderabad, Bangalore

Qualification: B. Tech /B.E in computer science or equivalent

Minimum 10+ years of experience in Advanced Java

At least 2+ years of experience for the following areas:

• Lead and mentor full-stack development teams across multiple projects and workstreams.
• Define technical architecture, coding standards, and development best practices.
• Drive end-to-end delivery of enterprise applications using Agile methodologies.
• Oversee application design, development, testing, deployment, and production support.
• Ensure adherence to security, performance, quality, and compliance standards.
• Collaborate with clients, product owners, architects, and cross-functional teams.
• Manage resource planning, risk mitigation, technical reviews, and stakeholder communication.
• Promote DevOps, CI/CD, and automation practices to improve delivery efficiency

Must Haves-

• Strong experience in Java Full Stack Development.
• Expertise in Spring Boot and Microservices Architecture.
• Proficiency in Python, Shell Scripting, and backend development.
• Hands-on experience with SQL, Oracle, and PostgreSQL databases.
• Front-end expertise in React, Angular, HTML5, CSS3, Bootstrap, and JSP.
• Experience with Kafka or similar event-driven messaging platforms.
• Strong understanding of API Design, REST Services, and Swagger/OpenAPI.
• Experience implementing security frameworks including OAuth 2.0.
• Hands-on expertise with Jenkins, CI/CD pipelines, and DevOps practices.
• Experience with code quality and security tools such as SonarQube and Fortify.
• Proven people management, stakeholder management, and delivery leadership experience.
• Experience working in Agile/Scrum environments.

Good to Haves-

• Experience with cloud platforms (AWS, Azure, or GCP).
• Knowledge of containerization and orchestration technologies such as Docker and Kubernetes/OpenShift.
• Experience with performance tuning, observability, and application monitoring tools.
• Telecom, OSS/BSS, or enterprise digital transformation domain experience.
• SAFe Agile, PMP, Scrum Master, or cloud certifications.
• Exposure to AI-assisted development tools and engineering productivity platforms.

About the company

Metron Security provides automation and integration services to leading Cyber Security companies. Our engineering team works on leading security platforms including - Splunk, IBM’s QRadar, ServiceNow, Crowdstrike, Cybereason, and other SIEM and SOAR platforms. 

Software Engineer is a challenging role within Cyber Security Engineering integration development. The role involves developing a product/service that achieves high-performance data exchange between two or more Cyber Security platforms. A Software Engineer is at the core of the evolution process and is responsible for the End-to-End delivery of the project, right from getting the requirements from customers to deploying the project for them on-prem or on the cloud, depending on the nature of the project. We follow the best practices of engineering and keep evolving. We are agile. 

Each integration needs reskilling yourself with the required technology for that project. If you are passionate about programming and believe in the best practices of software engineering, the following are the skills we are looking for: 

● Developer-centric culture - No bureaucracy or red tape. 

● Chance to work on 200+ security platforms. 

● Opportunity to engage with end-users (customers) and just a cog in the wheel.

About the role

We are looking for passionate developers with 4-7 years of experience in software development to join the Metron Security team as Software Engineers. 

Mandatory Skills 

• 6+ years of experience in software engineering, with a proven track record of leading engineering teams and mentoring junior developers. 
• Expertise in at least one or two Object-Oriented Programming language (Python, typescript, Java,Node.js,Angular, react.js C#, C++) . 
• Good knowledge of Data Structure and its correct usage. 
• Oversee code reviews, ensuring adherence to best practices and maintaining high code quality standards. 
• Imbibe and maintain a strong customer delight attitude while designing and building products/services.

Other Requirements 

• Open to learn any new software development skill if needed for the project.
• Alignment and utilisation of the core enterprise technology stacks and integration capabilities throughout the transition states. 
• Participate in planning, definition, and high-level design of the solution and exploration of solution alternatives. 
• Define, explore, and support the implementation of enablers to evolve solution intent, working directly with Agile teams to implement them. 
• Good knowledge of the implications of Cyber Security on production.
• Experience in architecting & estimating deep technical custom solutions & integrations. 
• Manage the customer to ensure we have a continuous flow of work from them so that the team has enough work for at least a month. 
• Mentor and coach team members, providing technical guidance and fostering professional development. 

Added advantage: 

• Experience in the Cyber Security domain.
• Experience in developing software using web technologies. 
• Experience in handling a project from start to end. 
• Hands-on experience in an Agile Development project and in writing and estimating User Stories. 
• Contribution to open source - Please share your link in the application/resume if any.

Job Description:

We are looking for a skilled Python Developer with 2+ years of hands-on experience in backend development and data processing. The ideal candidate should be proficient in Python and have working experience with web frameworks like Flask and FastAPI, along with exposure to data engineering and machine learning workflows.

Key Responsibilities:

Design, develop, and maintain scalable Python applications and APIs using Flask and FastAPI

Work with PySpark and Kafka for real-time data processing

Perform data manipulation and analysis using Pandas and NumPy

Develop and maintain modular, reusable, and testable code following OOP principles

Collaborate with data scientists to integrate ML models (TensorFlow, PyTorch, Scikit-learn) into production

Participate in code reviews, design discussions, and contribute to best practices

Write and maintain documentation for developed modules and workflows

Required Skills:

Strong proficiency in Python programming

Hands-on experience with Flask and/or FastAPI

Experience working with PySpark and Kafka

Solid understanding of Pandas, NumPy, and data handling in Python

Familiarity with TensorFlow, PyTorch, and scikit-learn

Good grasp of Object-Oriented Programming (OOP) concepts

Ability to write modular and maintainable code

Nice to Have:

Understanding of Machine Learning concepts and pipelines

Exposure to Generative AI (GenAI) technologies and tools

Experience with CI/CD tools, Docker, or cloud environments (AWS, GCP, etc.)

Qualifications:

Bachelor's degree in Computer Science, Engineering, or a related field

Job Title : SDE 3 – Infrastructure Platform Engineer

Experience : 5.5 to 8.5 Years

Number of Positions : 2

Employment Type : C2H (Contract to Hire)

Work Mode : Remote during contractual period → 5 Days WFO after conversion

Contract Duration : 3 Months

Post-Conversion Location : Pune

Notice Period : Immediate Joiners / Serving Notice Period / Up to 15 Days preferred

(Candidates officially serving a 30-day notice period may also be considered if they are on the bench and have a negotiable joining date)

Role Overview :

We are looking for an experienced SDE 3 – Infrastructure Platform Engineer to design, build, and operate scalable, secure, and highly reliable cloud infrastructure and internal platform capabilities.

The ideal candidate will have strong hands-on experience in Cloud Infrastructure, Infrastructure as Code (IaC), CI/CD, Docker, Kubernetes, automation, observability, networking, and distributed systems.

Mandatory Skills : AWS / Azure / GCP, Terraform / CloudFormation, Kubernetes, Docker, CI/CD, Platform / Infrastructure Engineering, Python / Go / Java / Ruby, Networking, Cloud Security, Distributed Systems, Scalability & Reliability, Strong Coding & Automation.

Key Responsibilities :

• Design and maintain scalable, highly available infrastructure on AWS / GCP / Azure.
• Build and manage Infrastructure as Code (IaC) using Terraform, CloudFormation, or similar tools.
• Develop automation for infrastructure provisioning, deployments, monitoring, and operations.
• Manage and optimize Docker and Kubernetes workloads.
• Build internal platform tools to improve developer productivity and engineering efficiency.
• Implement monitoring, logging, alerting, and observability solutions.
• Participate in incident response, RCA, postmortems, and reliability improvements.
• Design and improve CI/CD pipelines and deployment automation.
• Contribute to system design, architecture discussions, scalability, security, and cost optimization.
• Collaborate with application, data, and product engineering teams.

Required Skills :

• 5.5 to 8.5 years of experience in Infrastructure / Platform Engineering or similar roles.
• Strong hands-on experience with AWS, GCP, or Azure.
• Strong expertise in Terraform / CloudFormation.
• Experience with CI/CD, Docker, and Kubernetes.
• Strong programming skills in at least one of:
• Python, Go, Java, or Ruby.
• Good understanding of networking, cloud security, distributed systems, scalability, and reliability.
• Experience working with production infrastructure and highly available systems.
• Strong troubleshooting and problem-solving skills.

Nice to Have :

• Experience with SRE practices and production on-call ownership.
• Experience in fintech, payments, banking, or transaction-heavy systems.
• Knowledge of cloud security, compliance, or FinOps/cost optimization.
• Experience building internal developer platforms or productivity tools.
• Previous product company experience.

Interview Process :

Round 1 : Take-Home Coding Assignment – Submit within 48 hours

Round 2 : Coding Assignment Discussion – 1 Hour

Round 3 : Technical Managerial Round – 30 Minutes

Note : The take-home coding assignment is mandatory. Candidates should be comfortable completing and submitting the assignment within 48 hours before proceeding.

Ideal Candidate :

Strong Platform / Infrastructure Engineer with hands-on experience in :

Cloud + Terraform / CloudFormation + Kubernetes + CI/CD + Programming + SRE / Production Operations

Pure DevOps profiles without strong coding and platform engineering experience are not preferred.

Experience: 4+ Years 

Location: India (Bangalore, Hyderabad/ Mumbai/ Gurugram)

Role Summary:

AuxoAI is seeking a Senior GenAI Data Engineer with strong fundamentals in data engineering and end-to-end solution design. In this role, you will design and develop production-grade pipelines, leverage GenAI tools (Copilot, Claude, Gemini) to boost development productivity, and define engineering best practices across complex data environments. This is a highly collaborative, cross-functional role — ideal for someone who thrives at the intersection of data engineering excellence and GenAI-powered innovation.

Responsibilities:

• Architect and develop end-to-end data pipelines — from ingestion to transformation to consumption

• Lead solutioning and integration for complex data workflows (batch and streaming)

• Use AI-assisted coding tools (e.g., GitHub Copilot, Claude, Gemini) to accelerate code development, refactoring, and debugging

• Implement robust data quality, testing, lineage, and governance frameworks

• Drive best practices across pipeline performance, reusability, and scalability

• Mentor junior engineers and contribute to capability building within the data team

Requirement:

• 4+ years of experience in data engineering, with expertise in:

      o End-to-end pipeline development (batch and streaming)

      o Data modeling (dimensional, Data Vault, OBT)

      o ETL/ELT design patterns, performance tuning, and optimization

      o SQL (Advanced) and Python (Advanced)

      o Apache Spark for large-scale data processing

• Proficiency using AI coding tools (e.g., Copilot, Claude, Gemini) to enhance productivity and code quality

• Strong understanding of data quality frameworks, unit testing, and CI/CD for data workflows

• Experience with Google Cloud Platform services: o BigQuery, Dataflow, Cloud Composer, Pub/Sub, Dataproc, Vertex AI

• Exposure to finance or sales data domains

• Familiarity with Databricks, Delta Lake, or Apache Iceberg

• GCP Professional Data Engineer certification is a plus

Key Responsibilities

● Lead the architecture, design, development, and delivery of scalable backend services

using Python.

● Own technical direction and architectural decisions for backend systems and services.

● Design and build robust RESTful APIs, microservices, and distributed systems

capable of handling high-scale workloads.

● Design and implement real-time communication systems, including WebSocket-based

services, where required.

● Drive system performance, scalability, reliability, availability, and security.

● Lead performance optimization, capacity planning, monitoring, debugging, and

production issue resolution.

● Establish and promote best practices around code quality, testing, observability, CI/CD,

and production readiness.

● Collaborate closely with frontend, product, DevOps, infrastructure, and other

cross-functional teams to deliver end-to-end solutions.

● Mentor and provide technical guidance to engineers, contributing to overall team growth

and engineering excellence.

● Review code and architecture designs, identify technical risks, and drive improvements

across backend systems.

● Take ownership of complex technical problems and deliver reliable, maintainable,

production-grade solutions.

Required Skills & Qualifications

● 5+ years of software engineering experience, with significant experience in backend

development.

● Strong expertise in Python and experience building production-grade backend

applications.

● Proven experience designing and developing REST APIs and microservices

architectures.

● Strong understanding of distributed systems, scalability, fault tolerance, and

high-availability architectures.

● Hands-on experience with WebSockets and real-time backend integrations.

● Strong experience with SQL/NoSQL databases, caching systems, and data-intensive

applications.

● Experience with performance optimization, monitoring, logging, debugging, and

production operations.

● Strong understanding of software engineering principles, design patterns, and clean

architecture.

● Proven ability to lead technical initiatives and make sound architectural decisions.

● Strong communication, collaboration, and technical leadership skills.

● Experience mentoring engineers and conducting effective code and design reviews.

We are looking for a Python Backend Developer to design, build, and maintain scalable backend services and APIs. The role involves working with modern Python frameworks, databases (SQL and NoSQL), and building well-tested, production-grade systems.

You will collaborate closely with frontend developers, AI/ML engineers, and system architects to deliver reliable and high-performance backend solutions.

Key Responsibilities

• Design, develop, and maintain backend services using Python
• Build and maintain RESTful APIs using FastAPI
• Design efficient data models and queries using MongoDB and SQL databases (PostgreSQL/MySQL)
• Ensure high performance, security, and scalability of backend systems
• Write unit tests, integration tests, and API tests to ensure code reliability
• Debug, troubleshoot, and resolve production issues
• Follow clean code practices, documentation, and version control workflows
• Participate in code reviews and contribute to technical discussions
• Work closely with cross-functional teams to translate requirements into technical solutions

Required Skills & Qualifications

Technical Skills

• Strong proficiency in Python
• Hands-on experience with FastAPI
• Experience with MongoDB (schema design, indexing, aggregation)
• Solid understanding of SQL databases and relational data modelling
• Experience writing and maintaining automated tests
• Unit testing (e.g., pytest)
• API testing
• Understanding of REST API design principles
• Familiarity with Git and collaborative development workflows

Good to Have

• Experience with async programming in Python (async/await)
• Knowledge of ORMs/ODMs (SQLAlchemy, Tortoise, Motor, etc.)
• Basic understanding of authentication & authorisation (JWT, OAuth)
• Exposure to Docker / containerised environments
• Experience working in Agile/Scrum teams

What We Value

• Strong problem-solving and debugging skills
• Attention to detail and commitment to quality
• Ability to write testable, maintainable, and well-documented code
• Ownership mindset and willingness to learn
• Teamwork

What We Offer

• Opportunity to work on real-world, production systems
• Technically challenging problems and ownership of components
• Collaborative engineering culture