4,301 Python Jobs in India

We are looking for an AI Evaluation Engineer to evaluate, test, and improve the quality, reliability, and performance of large language models (LLMs) and generative AI applications.

You will design evaluation datasets, develop automated testing pipelines, analyze model outputs, and build metrics and tools to measure AI system performance across real-world use cases.

The ideal candidate has strong Python programming skills, an analytical mindset, and an interest in LLM evaluation, AI training, and data-driven model improvement.

Key Responsibilities

• Design, develop, and maintain evaluation datasets and test cases for LLMs and AI-powered applications.
• Evaluate model outputs for factual accuracy, relevance, reasoning, instruction following, consistency, and safety.

Required Qualifications

• 2+ years of experience in software development, data science, machine learning, or a related technical field.
• Strong proficiency in Python and experience with data-processing libraries such as pandas and NumPy.

Chief Engineer - Artificial Intelligence

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

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

Department

Technology & Product Engineering

Location

Hyderabad / Chennai

Reports to

Vice President - Technology

Experience

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

Role Summary

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

Key Responsibilities

1. AI Strategy and Architecture

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

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

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

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

2. Production AI Engineering

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

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

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

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

3. LLM, RAG and Agentic AI

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

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

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

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

4. AI Quality, Security and Responsible AI

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

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

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

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

5. AI Platform and Integration

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

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

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

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

6. Technical Leadership and Team Development

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

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

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

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

Required Skills and Experience

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

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

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

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

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

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

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

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

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

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

Good-to-Have Experience

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

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

·       Clinical Case Library, personalised learning or recommendation systems.

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

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

How Success Will Be Measured

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

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

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

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

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

We're hiring an AI/ML Mentor Intern for a well-established AI and data science training institute in KPHB, Hyderabad. Immediate joining.

What you'll do

• Mentor students in Python, machine learning, deep learning, NLP and computer vision

• Run doubt-clearing sessions, lab practicals and code reviews

• Help students build and debug real projects

• Prepare assignments, notebooks and assessments

Skills we're looking for

• Strong Python (NumPy, Pandas, scikit-learn)

• ML: regression, classification, clustering, model evaluation

• Deep learning with TensorFlow or PyTorch (CNNs, RNNs, Transformers)

• NLP and computer vision basics (OpenCV, Hugging Face)

• Statistics and probability

• Clear communication and patience in explaining concepts

Compensation: Up to ₹25,000 per month, based on performance. Internship leading to a full-time role.

Selection: online screening, technical interview, HR discussion.

Location: Pune/Bengaluru

As a Software Engineer, you will tackle a highly challenging role within our Cyber Security Engineering integration development team. You will be responsible for the End-to-End (E2E) delivery of projects from gathering customer requirements to deploying high-performance data exchange solutions on-prem or in the cloud. We are looking for a Systems-Level Thinker who can seamlessly transition between building complex integrations and architecting high-throughput, low-latency backends. Because each integration may require a different technical approach, we value engineers who love reskilling, following agile best practices, and maintaining an evolving mindset.

Core Responsibilities

Customer and Stakeholder Collaboration

• Customer Delight: Maintain a strong customer-first attitude while designing, building, and deploying products.
• Technical Communication: Articulate complex technical trade-offs clearly to both business stakeholders and engineering teams.
• Pipeline Management: Manage customer relationships effectively to ensure a continuous flow of project scope, maintaining clear team backlogs.

Job Requirements

• Experience: 3+ years of proven software engineering experience, with a track record of leading small engineering teams or mentoring junior devs.
• High-Throughput Backend Focus: 3+ years of experience engineering robust, real-time backends specifically using Go (Golang) or Java.
• Polyglot and Integration Capability: Deep expertise in at least one or two additional languages/frameworks from our ecosystem: Python, TypeScript, Node.js, React.js, Angular, C#, or C++.
• Computer Science Fundamentals: Excellent knowledge of complex Data Structures, algorithms, and their correct situational usage.
• Adaptability: A passionate programmer who is genuinely open and excited to learn new software development skills as required by changing project demands.

Bonus / Added Advantages

• AI & Intelligent Automation: Hands-on knowledge of AI concepts, Large Language Models (LLMs), and experience building or integrating AI agents to automate complex workflows or security processes.
• Cybersecurity Domain: Experience in the cybersecurity space (SIEM, SOAR, or platform security).
• Modern Web Tech: Strong experience in developing software using modern web technologies.
• E2E Lifecycle: Proven background handling a project completely from discovery to cloud/on-prem deployment.
• Open Source: Active contributions to the Open Source community. (Please share your GitHub/GitLab links in your application!)

Zeuron.ai – White Box Testing Intern (Software Systems)

Role Overview

Zeuron.ai is looking for 2 highly motivated interns with a strong foundation in software systems and

logical reasoning to work on white box testing of core product modules. This role involves working

directly with source code, validating system behavior, and ensuring robustness across AI-driven and

embedded platforms.

You will work closely with the core engineering team on real systems spanning AI, gaming, and

neuro-tech (MiMo ecosystem).

Key Responsibilities

• Perform white box testing on software modules

• Design and execute unit tests and integration tests

• Analyze source code to identify logical errors and edge cases

• Debug issues in collaboration with developers

• Write and maintain test cases and documentation

• Contribute to improving system reliability and performance

Required Skills

• Strong understanding of programming fundamentals

• Good knowledge of data structures and algorithms

• Proficiency in at least one programming language (Python / C++ / Java)

• Ability to read and understand existing codebases

• Logical thinking and problem-solving ability

Preferred Skills (Good to Have)

• Familiarity with unit testing frameworks

• Experience with Git or version control

• Exposure to automation or scripting

• Interest in AI, embedded systems, or game logic

Candidate Background

• B.Tech (CSE & Electronics)/ M.Tech/M.Sc (Computer Science)

• Strong academic foundation and interest in systems-level thinking

Internship Details

• Location: Bangalore (Electronic City)

• Duration: 6 months

• Start Date: November 16, 2026, or November 23, 2026

• Stipend: ₹15,000 per month

• Open Positions: 1

What You’ll Gain

• Hands-on experience with real-world production systems

• Exposure to AI + neuro-tech + gaming platforms

• Deep understanding of debugging and system validation

• Opportunity to work in a fast-paced deep-tech startup

How to Apply

Send your resume along with: - GitHub or project links (if any) - A short note on: “How would you test

a system if you had full access to its source code?”

JOB DESCRIPTION

Position: Full-Stack Developer + DevOps Engineer

Department: Customer Support

Location:Chennai

Employment Type: Full-Time

Experience: Min 5 years of experience

Job Summary

We are looking for a hands-on Full-Stack Developer with DevOps experience who can build, deploy, maintain, and scale web applications. The ideal candidate should have strong experience in React, Python, cloud infrastructure, CI/CD pipelines, and application deployment. The candidate will be responsible for developing frontend and backend applications while ensuring reliable deployments, infrastructure management, and production performance.

Key Responsibilities

1. Full-Stack Development

* Develop responsive and scalable web applications using React.

* Build and maintain backend services, APIs, and business logic using Python.

* Integrate frontend applications with backend services and databases.

* Write clean, reusable, maintainable, and well-tested code.

* Debug application issues and improve performance and security.

2. DevOps and Cloud Infrastructure

* Manage and maintain cloud infrastructure using AWS and/or Microsoft Azure.

* Build, configure, and maintain CI/CD pipelines for automated testing and deployment.

* Automate application builds, releases, and deployment workflows.

* Manage server environments, application hosting, monitoring, and logging.

* Troubleshoot production issues and ensure application availability and reliability.

* Implement infrastructure automation and deployment best practices.

3. Collaboration and Ownership

* Collaborate with engineering, product, and QA teams.

* Participate in code reviews, technical discussions, and release planning.

* Identify opportunities to improve development workflows and deployment efficiency.

* Take ownership of application development, infrastructure, and production support.

Required Skills

·       Strong hands-on experience with React.

·       Proficiency in Python and backend development.

·       Experience building and integrating REST APIs.

·       Practical experience with AWS and/or Microsoft Azure.

·       Hands-on experience configuring and managing CI/CD pipelines.

·       Understanding of cloud deployments, servers, networking, and application monitoring.

·       Familiarity with Git, version control, and collaborative development workflows.

·       Strong debugging, troubleshooting, and problem-solving skills.

Good to Have

·       Experience with Docker and Kubernetes.

·       Infrastructure as Code tools such as Terraform.

·       Experience with databases such as PostgreSQL.

·       Knowledge of Linux, scripting, security, and cloud cost optimization.

·       Experience with automated testing and production monitoring.

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

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

Key Responsibilities:

Architecture & Platform

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

Reliability Engineering

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

AI-First Engineering

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

Leadership & SDLC

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

Key Requirements:

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

Nice-to-Have

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

Why This Role?

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

Why this role exists 

Most systems work at a low scale. 

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

We are building a platform that must: 

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

What you’ll do 

You will not just write services. 

You will design and own core platform systems. 

1. Scale the platform without breaking architecture 

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

2. Build the workflow automation (WA) engine 

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

3. Build the insurance-specific data layer 

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

4. Make deployment and setup simple 

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

5. Create a compounding data advantage 

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

6. Own production reliability 

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

What success looks like 

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

Who you are 

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

What will make you stand out 

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

Why join 

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

What this role is not 

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

What this role is 

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

One question to self-evaluate 

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

We are seeking a skilled Automation Test Engineer with strong hands-on experience in Python-based automation frameworks. The ideal candidate should have solid experience in designing, developing, and maintaining automation test suites for web and API applications, ensuring high product quality and test coverage.

Key Responsibilities

Design, develop, and maintain automation test scripts using Python.

Develop and execute test cases for functional, regression, API, and integration testing.

Build and enhance test automation frameworks (Selenium / PyTest / Robot Framework etc.).

Perform API testing using tools like Postman, RestAssured, or Python requests library.

Collaborate closely with developers, BAs, and DevOps teams to ensure continuous integration and quality delivery.

Analyze test results, log defects, and track them to closure.

Participate in sprint planning, daily standups, and release execution.

Contribute to improving QA processes, tools, and standards.

Required Skills & Experience

3–4 years of experience in Automation Testing.

Strong programming skills in Python.

Hands-on experience with Selenium WebDriver.

Experience with automation frameworks like PyTest / Robot Framework / Behave.

Good understanding of API testing and automation (REST/JSON).

Experience working with CI/CD pipelines (GitLab CI, Jenkins, Azure DevOps, etc.).

Knowledge of version control (Git).

Familiarity with Agile development methodologies.

Strong debugging, analytical, and communication skills.

Nice to Have

Experience with performance testing tools (e.g., JMeter, Locust).

Working knowledge of Docker or cloud platforms (AWS/Azure/GCP).

Exposure to Mobile Application automation (Appium).

ISTQB Certification or equivalent is a plus.

Education

Bachelor’s degree in Computer Science, Engineering, or equivalent related field.

Full-Stack AI Engineer

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

Role Summary :

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

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

Key Responsibilities :

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

Essential Skills & Experience :

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

Preferred Skills :

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

Role Expectations :

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

Golang Developer

Experience: 6-8 years

Employment Type: Permanent, Full-time

Desired Skill: Golang,Python, GRPC, RestAPIs, AWS

Work Mode: Pune, India

Availability: Immediate Joiners

Must have skills:

● 6+years of Software Development experience

● 5+years of GoLang programming; Prefers additional proficiency in Python

● Knowledgeable in writing REST APIs

● Comfortable programming in production grade systems

● Experience with building HTTP based services

● Strong background of optimizing performance

● Familiarity with event-driven systems

● Experience dealing with highly concurrent, distributed architectures/systems.

Good to have skills:

• Exposure to relational databases
• Experience with Cloud Providers such as AWS is an advantage; cloud privileged access (CIEM, IAM roles, ephemeral credentials)
• Experience using Terraform to manage infrastructure as code would be an advantage
• Hands-on experience building or extending Privileged Access Management (PAM) capabilities — credential vaulting, secrets management, password rotation, just-in-time / time-bound privileged access
• Working knowledge of privileged session management and session recording — session proxying/brokering, keystroke and video capture, session replay, live monitoring and termination, tamper-evident audit trails
• Familiarity with remote access protocols and gateways — SSH, RDP, HTTPS/web-based sessions; protocol proxying and man-in-the-middle session interception

JOB REQUIREMENTS • 10+ years of experience in software development, with at least 5 years in as a Development Lead, Engineering Manager, or similar leadership role. • Strong hands-on technical background in backend/frontend/cloud technologies. • Understanding of cloud platforms (AWS/Azure/GCP) and microservices architecture. • Deep understanding of SDLC, Agile methodologies, version control, and DevOps practices, containers, CI/CD, and scalable architectures. • Excellent leadership, decision-making, and project management, problem solving skills. • Strong communication skills with the ability to present technical and business information clearly. • Ability to handle multiple projects and thrive in a fast-paced environment. • Strong ownership mindset with a focus on delivering high-quality outcomes. • Passion for mentoring, building teams, and improving engineering culture. JOB RESPONSIBILITIES Team Leadership & People Management • Lead, mentor, and manage the entire development team, including interns, junior developers, and senior engineers. • Conduct regular training sessions, knowledge-sharing meetings, and capability-building workshops. • Identify skill gaps and create growth plans for team members. • Manage performance reviews, provide feedback, and support career progression. • Create a culture of ownership, accountability, and high performance. Project & Delivery Management • Own the entire Software Development Life Cycle (SDLC) from planning to deployment. • Break down product requirements into sprint tasks and assign responsibilities. • Define and manage project deadlines, delivery milestones, and development roadmaps with the team. • Ensure timely delivery of high-quality features aligned with product goals. • Work closely with the CEO for project planning, updates, and escalations. • Ensure alignment between business needs and technical solutions. Technical Leadership • Provide architectural direction for scalable, secure, multi-tenant, multi-region systems. • Review code, ensure adherence to coding standards, and drive continuous improvements. • Evaluate and implement new technologies to keep the product stack modern and efficient. • Ensure best practices in security, performance, documentation, and DevOps pipelines. • Lead R&D initiatives for new features, tools, or tech stacks. Process & Quality Ownership • Implement and refine engineering processes, coding guidelines, and development workflows. • Ensure strict adherence to SDLC, secure development practices, and code review processes. • Introduce automation where possible (CI/CD, testing, deployment flows). • Drive continuous improvement in team productivity and software quality. • Conduct root-cause analysis and lead improvements to reduce bugs and downtime. Communication & Reporting • Act as the primary communication bridge between the CEO and development team. • Provide weekly project reports, progress updates, risk assessments, and performance insights. • Maintain transparency and clarity in project communication across the organization. Cross-Functional Collaboration • Work directly with the CEO, Product leadership, and other department heads. • Align technical decisions with business objectives and customer needs. • Support SOC, support teams, and clients for escalations when required. Working Days & Time: Monday to Friday – 10AM to 7PM. WHAT WE OFFER • Opportunities to learn and grow in a professional environment. • Exposure of International market • 5 days working • Friendly work environment • PF benefits • Employee Referral Bonus • Monthly Engagement Activities • Festival Celebrations • Leave Encashment  

Technical Architect – Product Engineering

Experience: 15+ Years

Location: Pune, India

Employment Type: Full-time

Desired Skills: Python, Technical Architecture, AWS, Microservices, SaaS / Multi-tenant Architecture, Kubernetes, System Design

About the Role

We are looking for a Senior Technical Architect to lead the architecture, design, and technical evolution of an enterprise SaaS product. This is a hands-on leadership role requiring deep technical expertise, strong product engineering experience, and the ability to build scalable, secure, and high-performance platforms.

The ideal candidate should be passionate about solving complex engineering problems, driving innovation, mentoring development teams, and effectively leveraging AI to accelerate software development.

Key Responsibilities

• Own the overall product architecture and technical roadmap.
• Design and build scalable, secure, and highly available enterprise applications.
• Lead the design and implementation of new product features from concept to production.
• Remain hands-on with coding and contribute to critical product components.
• Drive architecture reviews, code quality, performance optimization, and engineering best practices.
• Lead cloud architecture, security, scalability, and DevOps initiatives.
• Evaluate and adopt modern technologies to improve product capabilities and engineering efficiency.
• Leverage AI tools (ChatGPT, GitHub Copilot, Cursor, Claude, etc.) to accelerate software development, code reviews, testing, documentation, debugging, and productivity.

Required Skills & Qualifications

• 15+ years of software product engineering experience with at least 5 years in a Technical Architect role.
• Strong hands-on expertise in Python and modern backend frameworks.
• Deep experience with AWS services and cloud-native application architecture.
• Strong understanding of DevOps, CI/CD pipelines, Infrastructure as Code (Terraform/CloudFormation), Docker, Kubernetes, and container orchestration.
• Experience designing microservices, REST APIs, event-driven architectures, and distributed systems.
• Strong knowledge of SQL and NoSQL databases.
• Experience with scalable SaaS platforms, multi-tenant architectures, and secure application design.
• Excellent understanding of software design patterns, performance tuning, observability, and system reliability.
• Strong analytical, problem-solving, and decision-making skills.

Job Title : Senior AWS Data Engineer – Data Lake Platform

Experience : 5+ Years

Location: Gurugram Sector 43, Haryana

Work Mode : Work From Office (5 Days a Week – Monday to Friday)

Open Positions : 8+

About the Role :

We are looking for a skilled Senior AWS Data Engineer with strong hands-on experience in building, managing, and optimizing enterprise-scale data lake platforms on AWS.

The ideal candidate will have expertise in AWS data services, PySpark, Apache Airflow, and large-scale data pipeline development. The role involves designing end-to-end data ingestion and processing workflows, maintaining data quality, optimizing platform performance, and supporting analytics and downstream data consumption requirements.

Mandatory skills :

AWS Data Lake, Amazon S3, EMR, Glue, Athena, Redshift, DMS, Lambda, RDS, IAM, PySpark, Apache Spark, Apache Airflow, Python, Advanced SQL, Data Modeling, Production Data Pipelines, Hasura/GraphQL, PostgreSQL, and Production Support.

Key Responsibilities :

• Design, develop, and maintain scalable AWS-based data lake platforms and end-to-end data pipelines.
• Build data ingestion, staging, transformation, curated, and consumption layers using AWS services.
• Develop and optimize data processing pipelines using PySpark, Apache Spark, and AWS EMR.
• Implement workflow orchestration and scheduling using Apache Airflow.
• Work with Amazon S3, AWS Glue, Glue Data Catalog, Amazon Athena, and Amazon Redshift for data storage, cataloging, processing, and analytics.
• Develop efficient SQL queries and implement data modeling strategies for enterprise reporting and analytics.
• Build and support data-serving solutions using Amazon RDS, AWS Lambda, API Gateway, and PostgreSQL-based platforms.
• Monitor pipeline performance, troubleshoot production issues, perform root-cause analysis, and ensure data pipeline SLAs.
• Implement data security, access controls, PII protection, and governance best practices across the platform.
• Optimize data processing performance, query execution, storage utilization, and AWS infrastructure costs.
• Collaborate with application, analytics, and business teams to deliver reliable and scalable data solutions.

Mandatory Skills :

• AWS Data Services : Amazon S3, EMR, Glue, Athena, Redshift, DMS, Lambda, RDS, and IAM.
• Data Engineering : Strong hands-on experience building and maintaining enterprise data lake platforms.
• Programming : Python, PySpark, and Apache Spark.
• Orchestration : Production experience with Apache Airflow.
• Database & SQL : Advanced SQL, data modeling, and query optimization.
• Data Architecture : Experience with data ingestion, staging, transformation, curated layers, and consumption architecture.
• Production Support : Pipeline monitoring, troubleshooting, root-cause analysis, and SLA management.
• API / Data Serving : Experience with Hasura or a similar GraphQL-based data-serving layer integrated with PostgreSQL.
• Platform Ownership : Ability to independently manage data pipelines, improve platform reliability, and collaborate with cross-functional teams.

Good-to-Have Skills :

• Experience with dbt for data transformation and modeling.
• Knowledge of data lakehouse architectures and table formats such as Apache Iceberg, Delta Lake, or Apache Hudi.
• Experience with Amazon Redshift workload optimization, distribution keys, sort keys, and Spectrum.
• Knowledge of Kafka and real-time or streaming data ingestion.
• Experience with PostgreSQL or Amazon Aurora as a data-serving layer.
• Familiarity with data governance, compliance, and sensitive-data management.
• Experience in the BFSI or health insurance domain.

Ideal Candidate Profile :

• 5+ years of hands-on experience in AWS Data Engineering.
• Strong experience building and supporting production-grade AWS data lake platforms.
• Practical expertise in PySpark, Apache Airflow, SQL, and AWS data services.
• Ability to troubleshoot complex data pipeline issues and optimize performance.
• Strong understanding of data architecture, data modeling, and production support practices.
• Candidates with experience in enterprise data platforms and insurance or BFSI environments will be preferred.

Our Story

At The Alter Office, we build what comes next. We operate as an internal innovation lab, creating stealth products, new business bets, and high-leverage systems designed to unlock disproportionate value for us and our partner company ITW Consulting.

Our work is not centered around being a conventional service partner. Instead, we focus on building products and platforms that solve complex, strategic problems and create long-term advantage. Where needed, we have stepped in on critical opportunities beyond the usual scope, especially when speed, product thinking, and execution depth mattered most.

About the Role

We are building a holistic AdTech platform that delivers premium value to both advertisers and publishers, and the backend is where that entire ecosystem actually runs - the ad marketplace, campaign creation, ad-serving decisioning, analytics collection, attribution, and ROAS measurement.

Concretely, that means large-scale architecture: the ad-serving systems that make real-time decisioning calls at volume, the scalable data platforms that ingest and process billions of events a day, the analytics platforms that turn that data into attribution and ROAS numbers advertisers and publishers trust, and the autonomous AI agents we're building to automate campaign optimization and decisioning across the platform.

We are looking for someone who is eager to learn, enjoys solving technical problems, and wants to grow beyond simply implementing tasks. You'll have opportunities to understand how backend systems connect to the product and gradually take ownership of larger parts of the platform.

Key Responsibilities

• Build and maintain backend APIs and services for our ad marketplace, campaign management, and analytics platforms.
• Work with senior engineers to design and implement scalable backend solutions.
• Develop RESTful APIs and asynchronous backend workflows.
• Work with SQL databases such as MySQL and PostgreSQL and NoSQL technologies such as MongoDB and Redis.
• Implement data models, database queries, caching, and basic performance optimizations.
• Contribute to backend infrastructure supporting analytics, attribution, and AI-powered platform features.
• Collaborate with product, frontend, backend, and DevOps teams to deliver end-to-end features.
• Implement authentication, authorization, and basic security practices under the guidance of senior engineers.
• Write clean, maintainable, documented, and tested code.
• Use Git and participate in code reviews and team development practices.
• Learn and contribute to deploying backend services on cloud platforms such as AWS, GCP, or Azure.
• Work with Docker for containerizing backend services.
• Contribute to CI/CD pipelines and development workflows.
• Help monitor, debug, and troubleshoot backend services in development and production environments.
• Explore event-driven and distributed architectures using technologies such as message brokers, WebSockets, or GraphQL where appropriate.

Requirements

• 1–2 years of professional backend engineering experience, including relevant internship or project experience.
• Proficiency in at least one backend language, with the ability and willingness to adapt to other languages such as Node.js/JavaScript, Go, Python, and Java.
• Good understanding of RESTful API design and backend fundamentals.
• Good understanding of asynchronous programming and how backend services communicate.
• Familiarity with relational databases such as MySQL or PostgreSQL.
• Familiarity with at least one NoSQL database such as MongoDB or Redis is a plus.
• Good understanding of data modeling and writing SQL queries.
• Familiarity with Git and software development workflows.
• Good understanding of Docker and containerized applications.
• Exposure to cloud platforms such as AWS, GCP, or Azure is a plus.
• Understanding of basic backend security concepts such as authentication, authorization, and secure API practices.
• Strong problem-solving and debugging skills.
• Good communication and willingness to collaborate with other engineers and product teams.
• Strong learning mindset and willingness to work with unfamiliar technologies.
• Comfortable working in a fast-paced environment with evolving priorities.

5 steps, and we tell you where you stand at each one.

Online Assessment : Evaluate coding skills, backend fundamentals, SQL, problem-solving, and technical understanding.

Technical Interview 1 : Discuss previous projects, backend experience, APIs, databases, system design, and production experience.

Take-Home Assessment : A practical backend assignment to evaluate code quality, architecture, scalability, testing, and ability to build a production-ready solution.

Technical Interview 2 : Deep dive into the take-home assignment, system design, technical decisions, scalability, debugging, cloud, and architecture.

HR Interview : Discuss communication, ownership, culture fit, career goals, compensation, availability, and overall expectations.

Full Stack Developer (SaaS Integrations)

1-2 years of experience

Role: Build and maintain integrations between SaaS applications using REST APIs, webhooks, SDKs, and Workato. You’ll turn customer requirements into working integrations and build supporting React.js components when needed.

Responsibilities:

• Develop Python backend services and integration scripts
• Build and maintain Workato recipes and automation workflows
• Handle authentication (OAuth 2.0, JWT, API keys) and data formats (JSON, CSV, XML)
• Map and transform data between systems, and reconcile it to confirm it moved accurately
• Troubleshoot API, authentication, and mapping failures
• Add error handling, retries, logging, and monitoring
• Flag API limitations and technical risks early
• Document integrations, join code reviews, and work with Tech Leads, QA, and stakeholders

Required skills:

• Python, with FastAPI, Flask, or Django
• Strong REST API knowledge: HTTP methods, status codes, headers, pagination, rate limits, webhooks
• Postman or similar tools
• React.js and JavaScript
• Basic SQL (PostgreSQL or MySQL)
• Git

Good to have: Workato experience (not mandatory if you’re willing to learn). Experience with MuleSoft, Boomi, Zapier, Make, or n8n also counts.

Competencies: Problem-solving, independent API troubleshooting, clear communication, ownership, and a strong learning attitude.

Qualification: B.E / B.Tech / MCA / B.Sc / M.Sc in Computer Science, IT, or a related field.

Growth: The role can lead to Integration Engineer or SaaS Implementation Engineer.

Position Overview:

We are building a new retail merchandising platform on top of that data. It answers what to stock, how much,

and in which store—combining sales, catalogue, and customer data with GeoIQ’s location attributes at retail

scale: thousands of stores, tens of thousands of SKUs, decisions made weekly.

As part of the data science team on this platform, you will build the forecasting, assortment and

recommendation models behind those decisions. The platform is new, so the models are being built now, not

maintained. Hands-on modelling with senior review — what you ship changes what a store actually orders.

Responsibilities:

● Build SKU- and store-level demand forecasts, including for new products with little or no sales history.

● Build assortment models — which products earn shelf space in which stores or store clusters, and how

a range change is likely to play out.

● Build recommendation and ranking models for product discovery, cross-sell and bundling, including

cold-start for new products and customers.

● Engineer features from sales, seasonality, promotions, pricing, catalogue hierarchy, store attributes and

GeoIQ’s location and demographic layers.

● Handle the realities of retail data: intermittent demand, stockouts censoring true demand, returns and

cannibalisation between similar SKUs.

● Design backtests and A/B tests that reflect how planners use the output; monitor deployed models for

drift.

● Build data pipelines and work with engineering to take models to production.

● Communicate findings to merchandising, category, and product teams.

Expectations:

● Proficient in Python

● Work experience: 1–3 years

● Prior experience with building ML models end-to-end

● Prior experience with SQL

● Knowledge of statistical techniques and model evaluation

● Experience with time-series forecasting or recommender systems will be an added advantage

● Experience with retail, e-commerce, supply chain, or spatial data will be an added advantage

Join us early and help build the merchandising brain for retail at national scale — close to the product and the

customer, with the freedom of a platform still being shaped.

About the Role

We're looking for engineers who can independently design and build reliable backend services. Beyond writing code, you should be comfortable thinking about performance, data consistency, reliability, and maintainability.

Responsibilities

● Design and implement backend services.

● Translate business requirements into technical solutions.

● Design efficient database schemas.

● Build reliable asynchronous workflows.

● Debug production issues independently.

● Review code and mentor junior engineers.

● Improve application performance and reliability.

● Contribute to technical design discussions.

Must Have Strong Programming Skills

● Proficiency in at least one backend language.

● Strong Object-Oriented Design.

● Good understanding of design principles.

● REST API design.

● Writing maintainable, testable code.

Database Knowledge Comfortable with:

● Database design

● Query optimization

● Transactions

● Indexing strategies

● Locking (high-level understanding)

● Isolation levels (basic understanding)

● Data modelling Concurrency

Working knowledge of:

● Race conditions

● Concurrent updates

● Idempotency (basic understanding)

● Optimistic vs pessimistic locking (conceptual)

● Thread safety (language dependent)

Asynchronous Systems Experience with:

● Background jobs

● Queues

● Retry mechanisms

● Scheduled jobs

● Event-driven workflows (nice to have)

Problem Solving Should be comfortable:

● Debugging production issues.

● Reading logs.

● Identifying bottlenecks.

● Breaking large features into smaller tasks.

● Evaluating trade-offs before implementation.

Good to Have Experience with:

● Redis

● RabbitMQ / Kafka / BullMQ or similar

● Docker

● Kubernetes

● AWS

● CI/CD

● Monitoring & Logging tools

What We Look For Successful engineers here typically:

● Think before coding.

● Write maintainable solutions.

● Understand why a design works, not just how.

● Consider edge cases.

● Take ownership of production issues.

● Help improve the engineering practices of the team.

Interview Focus

● Programming fundamentals

● Database design

● SQL

● Concurrency scenarios

● API design

● Production debugging

● Problem-solving exercise

● Code review discussion

About Orenda

Orenda is a fintech-enabled financial services company founded in 2017 and based in Ahmedabad, Gujarat. We work as a corporate DSA and channel partner for leading banks and NBFCs, helping individuals, professionals, and MSMEs access suitable financial solutions across business loans, personal loans, home loans, loan against property, and professional loans.

At Orenda, we combine financial expertise, technology, and streamlined processes to simplify the lending journey. We are building our own lending-tech platform to improve operational efficiency, strengthen lender and partner integrations, and develop technology-driven solutions that support our evolving business needs.

About the role

We're looking for a Lead Software Engineer who enjoys building as much as designing. You'll shape how our systems are architected, write a good share of the code yourself, and lead a team of 3 to 5 engineers, including AI/ML engineers.

This is a hands-on leadership role, not a pure management or architecture position. Your time will be roughly split like this:

Share of time

Leading the team ~30%

Solution design ~30%

Hands-on coding ~30%

Deployment and infrastructure~10%

What you'll work on

Solution design and architecture

• Turning business needs into technical designs that are practical to build and easy to maintain

• Making architecture decisions across services, integrations and data flows

• Estimating, scoping and planning new features with business and product stakeholders

• Shaping the solution design for AI/ML use cases alongside the AI/ML engineers

Engineering and delivery

• Writing production code in Python and Node.js

• Rolling out new features across our internal and partner-facing platforms, including our CRM and partner portal

• Continuously improving existing systems for performance, reliability and code quality

• Reviewing code and setting engineering standards for the team

Infrastructure and cloud

• Maintaining and upgrading our infrastructure, including a planned move to a major cloud platform

• Owning deployments and production stability together with the team

• Working with event-driven and messaging systems (NATS today, Kafka planned)

Team leadership

• Leading and mentoring a team of 3 to 5 engineers

• Planning and prioritising work, unblocking the team, and making sure things ship

• Building a culture of ownership, clear documentation and quality

What we're looking for

• 5 to 8 years of software engineering experience, with hands-on coding in your recent roles

• Strong command of Python and Node.js

• Proven experience designing and building backend systems and microservices that run in production

• Hands-on experience deploying and running workloads on at least one major cloud platform (AWS, Azure or GCP)

• Solid working knowledge of PostgreSQL

• Experience with messaging or event streaming systems such as NATS, Kafka or RabbitMQ

• Experience leading or mentoring a small engineering team

• Comfort estimating effort, breaking down features and planning delivery

• Enough understanding of AI/ML systems to guide their solution design and integration

• Clear communication with both technical and non-technical stakeholders

Good to have

• Experience working at a fintech, lending or financial services company

• Hands-on experience with Kafka

• Experience leading an infrastructure upgrade or cloud migration

• Experience building or scaling CRM or partner-facing portal products

Why Join Us?

• Build a growing lending-tech platform: Play a key role in shaping the technology behind a growing financial services business.
• Own technical decisions: Contribute directly to architecture, engineering standards, and technology direction.
• Stay hands-on: Combine solution design and technical leadership with meaningful coding responsibilities.
• Work with emerging technologies: Collaborate with AI/ML engineers and contribute to evolving platform capabilities.
• Lead and grow a team: Mentor engineers and help build a strong engineering culture as the technology function scales.
• Make a measurable impact: Build systems that improve operational efficiency and support business growth.

Snowflake Administrator

What You’ll Do

• Observability: Monitor Snowflake queries, virtual warehouses, tasks, data loads, and overall account health. Identify and resolve operational issues.
• FinOps & Cost Optimization: Monitor credit consumption, storage, and warehouse costs. Optimize warehouse sizing, auto-suspend settings, and resource monitors.
• User Management: Manage Snowflake users, roles, onboarding, offboarding, and Role-Based Access Control (RBAC).
• Privilege Access Management: Review grants, privileged roles, access policies, and audit logs to enforce the principle of least privilege.
• Platform Maintenance: Maintain Snowflake account settings, integrations, and routine operational health checks.
• Service Desk Management: Triage incidents and service requests, investigating query failures, access issues, and platform-related problems.
• Enhancements & Automation: Improve Snowflake configurations, automate operational tasks, and streamline support processes.
• Business Continuity & Recovery: Support backup and retention policies, Time Travel, Fail-safe, and data recovery procedures.
• Deployment & CI/CD: Support controlled releases of Snowflake objects, roles, scripts, and configurations through CI/CD pipelines.
• Data Load Troubleshooting: Resolve issues related to Snowpipe, COPY commands, stages, file formats, connectivity, and scheduled data loads.
• Transformation & Data Model Support: Perform first-line troubleshooting of failed tasks, SQL errors, and schema changes.
• Functional Data Support: Investigate initial data availability and quality issues, coordinating with data owners for resolution.
• Project Support: Assist engineering teams with Snowflake environments, integrations, and migrations.
• Documentation: Maintain runbooks, access management procedures, operational guides, and knowledge base articles.

What We’re Looking For

• 5+ years of experience in data platform administration, operations, or production support, including hands-on Snowflake experience.
• Strong knowledge of Snowflake administration, including RBAC, virtual warehouses, query history, performance tuning, and cost optimization.
• Hands-on experience with Snowflake data loading, stages, tasks, Snowpipe, and cloud platforms such as AWS or Azure.
• Proficiency in SQL and familiarity with Python for scripting and automation.
• Experience with CI/CD pipelines, Jira, ITSM processes, and monitoring or automation tools.
• Strong troubleshooting, documentation, communication, and stakeholder management skills.

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

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

What You'll Do:

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

What We're Looking For:

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

What Makes This Role Different:

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

We're looking for someone who:

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

Location & Compensation

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

Interview Process:

3 Rounds

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

Data Scientist – Machine Learning & Applied Analytics. 

Location: Bengaluru 

Experience: 5–8 Years 

Role Type: Full-Time 

Business Unit: Products & Platforms (PMG) 

Role Overview 

We are looking for a Data Scientist – Product Analytics & Machine Learning to help build differentiated analytics and ML capabilities across our product and platform portfolio, including MOBIUS+ and Signate. 

This is a hands-on product-focused role responsible for translating real-world customer and domain problems into scalable analytics and machine learning solutions. The role will work across the complete lifecycle — from data exploration and experimentation through model development, validation, productization and production monitoring. 

The Data Scientist will also work closely with Tata Elxsi's internal analytics teams, specialist solution providers and academic/research institutions to evaluate, integrate and evolve analytical capabilities as part of our products. 

Key Responsibilities 

Product Analytics & ML 

• Translate product and customer problems into well-defined analytics and ML use cases. 
• Perform data exploration, feature engineering, statistical analysis and experimentation. 
• Develop, train, validate and optimize machine learning and predictive models. 
• Define appropriate model performance metrics, benchmarks and acceptance criteria. 
• Convert prototypes and experiments into scalable, production-ready capabilities. 
• Work with Product, Architecture and Engineering teams to integrate models and analytics into SaaS products and platforms. 

Model Evaluation & Productization 

• Evaluate models and analytical solutions developed by internal teams, technology partners and specialist solution providers. 
• Assess model assumptions, data requirements, accuracy, robustness, explainability and limitations. 
• Benchmark alternative models/approaches and provide evidence-based recommendations. 
• Establish practices for model versioning, validation, monitoring, drift detection and continuous improvement. 
• Ensure that externally sourced models can be effectively integrated, governed and evolved within the product. 

Collaboration & Research 

• Collaborate with Tata Elxsi's broader AI, analytics and domain teams and leverage specialist capabilities where required. 
• Work technically with external solution providers to understand and integrate their algorithms and models. 
• Engage with researchers and academic institutions such as IITs, NITs and IISc on advanced analytics and ML opportunities. 
• Evaluate research, algorithms and PoCs and help translate promising approaches into production-grade product capabilities. 
• Build reusable analytical assets, datasets, features, evaluation frameworks and know-how across the product portfolio. 

Technical Skills 

• Strong foundation in statistics, probability, machine learning and data analysis. 
• Strong hands-on programming skills in Python and common data science libraries. 
• Experience with Pandas, NumPy, scikit-learn and relevant ML frameworks. 
• Experience developing predictive models using structured and time-series data. 
• Understanding of supervised/unsupervised learning, anomaly detection, forecasting, classification and regression techniques. 
• Experience with feature engineering, model selection, hyperparameter optimization and model evaluation. 
• Good understanding of model explainability, bias, uncertainty and robustness. 
• Working knowledge of SQL and large-scale data processing. 
• Experience deploying or integrating ML models into production applications through APIs, services or ML pipelines. 
• Understanding of MLOps, including model versioning, experiment tracking, monitoring and model lifecycle management. 
• Experience with cloud environments, preferably AWS, is desirable. 
• Exposure to GenAI/LLMs and their application within product analytics is an advantage. 

Product & Engineering Mindset 

• Ability to move beyond experimentation and think about how analytics becomes a repeatable product capability. 
• Strong problem-solving ability and comfort working with incomplete or imperfect real-world datasets. 
• Ability to distinguish between an interesting analytical result and one that creates measurable customer/product value. 
• Comfortable working closely with Product Managers, Domain SMEs, Architects and Software Engineers. 
• Ability to critically evaluate third-party algorithms and models rather than treating external solutions as black boxes. 
• Strong technical communication skills and ability to explain analytical concepts and model outcomes to both technical and business stakeholders. 

Preferred Experience 

• 5–8 years of relevant experience in Data Science, Machine Learning, Applied Analytics or related roles. 
• Experience building ML/analytics capabilities that have been deployed into production products or platforms. 
• Experience working with automotive, mobility, connected vehicle, battery/EV, IoT or industrial datasets is desirable but not mandatory. 
• Experience collaborating with technology partners, research organizations or academic institutions is an advantage. 
• Master's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering or a related quantitative discipline preferred. 

What Success Looks Like 

The successful candidate will help PMG establish a strong internal Data Science & ML capability that can build differentiated analytics, intelligently leverage Tata Elxsi's broader capabilities and external specialists, and retain the knowledge and ownership required to continuously evolve analytics as a core part of our products and platforms. 

Strong Data Engineer (AWS) Profile

2

Mandatory (Experience 1) – Must have minimum 6+ years of experience in Data Engineering, with strong experience designing, developing, and maintaining scalable data pipelines and ETL processes.

3

Mandatory (Experience 2) – Must have 3+ years of hands-on experience with AWS data engineering services, particularly S3, AWS Glue, EMR, Lambda, and Redshift.

4

Mandatory (Experience 3) – Must have strong programming experience in Python, Java, or Scala, with hands-on development of data processing and pipeline solutions.

5

Mandatory (Experience 4) – Must have strong expertise in SQL, data warehousing, and database technologies, including experience with both SQL and NoSQL databases.

6

Mandatory (Experience 5) – Must have hands-on experience working with Big Data technologies and distributed data processing, including designing and optimizing large-scale data pipelines.

7

Mandatory (Experience 6) – Must have experience with data pipeline troubleshooting, monitoring, data quality, governance, and security best practices.

8

Mandatory (Education) – B.Tech / B.E./ M.Tech

About the Role

We are looking for an AI/ML Engineer with 4+ years of Strong hands-on experience building and deploying production-grade AI systems. The ideal candidate should have strong expertise in Computer Vision, Generative AI, RAG pipelines, Voice AI, and LLM-powered applications, with experience delivering scalable, production-ready solutions across enterprise, healthcare, or SaaS environments

Key Responsibilities

• Design, develop, and deploy production-ready AI/ML and Generative AI applications, Computer Vision solutions.
• Build and optimize LLM-powered applications for real-world business use cases.
• Develop and maintain RAG (Retrieval-Augmented Generation) pipelines using vector databases and embedding models.
• Build Voice AI solutions including speech-to-text (STT), text-to-speech (TTS), conversational AI, and voice-enabled assistants.
• Create and optimize prompt engineering strategies to improve LLM output quality, consistency, and reliability.
• Work with open-source LLMs for inference, fine-tuning, evaluation, and deployment.
• Implement model monitoring, evaluation, guardrails, and performance optimization.
• Collaborate with DevOps and cloud teams for scalable deployments.
• Optimize AI systems for latency, cost, scalability, and production performance.
• Integrate AI services through APIs and enterprise applications.

Required Skills & Experience

• 4+ years of experience in AI/ML engineering and production deployments.
• Strong experience in Python and AI/ML development.
• Hands-on experience with Generative AI and LLM applications.
• Strong hands-on experience in Computer Vision using Python and frameworks such as OpenCV, PyTorch, and TensorFlow.
• Experience with Computer Vision tasks such as object detection, image classification, image segmentation, and feature extraction.
• Familiarity with models and libraries such as YOLO, Detectron2, MMDetection, and torchvision.
• Experience with image preprocessing, data augmentation, model training, evaluation, and inference optimization.
• Exposure to OCR technologies such as Tesseract or EasyOCR and vision-based deep learning models is an advantage.
• Experience building RAG pipelines using:
• Vector Databases: Pinecone, Weaviate, FAISS, ChromaDB, Milvus
• Embeddings and retrieval optimization
• Experience with Prompt Engineering techniques for LLM optimization.
• Experience with Open Source LLMs such as:
• Llama, Mistral, Falcon, Gemma, DeepSeek, Qwen
• Experience with Voice AI technologies:
• Speech-to-Text (Whisper, Deepgram, Google STT)
• Text-to-Speech (ElevenLabs, Azure Speech, Amazon Polly)
• Conversational Voice Agents
• Experience using frameworks/tools:
• LangChain, LangGraph, LlamaIndex, Hugging Face
• Understanding of fine-tuning, model evaluation, inference optimization, and AI observability.
• Experience deploying applications using:
• Docker, Kubernetes, CI/CD
• AWS / Azure / GCP

Preferred Qualifications

• Experience delivering AI solutions for Healthcare, Enterprise, or SaaS platforms.
• Exposure to MLOps practices and model lifecycle management.
• Understanding of AI governance, security, and responsible AI practices.
• Experience integrating AI with APIs and production services.

Nice to Have

• Knowledge of agentic AI workflows and orchestration.
• Experience with monitoring and evaluation frameworks.
• Exposure to multimodal AI applications

Education Qualifications

• B.Tech / M.Tech in CSE / IT / AI&ML only from good college.

Job Summary

We are looking for an experienced Data Engineer to build and optimize scalable data pipelines and AWS-based data platforms.

Key Responsibilities

• Develop and maintain data pipelines using Python and PySpark.
• Design and implement data lakehouse solutions on AWS.
• Build and manage data workflows using AWS Glue, EMR, ECS, and Step Functions.
• Work with DynamoDB and other data storage technologies.
• Monitor data pipelines and ensure data quality, performance, and reliability.
• Collaborate with stakeholders and engineering teams to deliver data solutions.

Mandatory Skills

• 5+ years of overall professional experience.
• 3+ years of experience in data platforms and big data technologies.
• Strong proficiency in Python and PySpark.
• Hands-on experience with AWS EMR, ECS, Glue, Step Functions, and DynamoDB.
• Experience designing and implementing AWS data lakehouse architectures.

Good to Have

• Apache Spark and Apache Iceberg.
• AWS Lambda, EventBridge, Kinesis, and Redshift.
• Experience with real-time data pipelines and event-driven architectures.

🚨 HIRING | Data Engineer – Amazon EMR 🔥

We are looking for experienced Data Engineers with strong hands-on expertise in Amazon EMR, Python, and Scala.

📌 JOB DETAILS:

💼 Experience: 6+ Years

💰 CTC: Up to 30 LPA

📍 Location: Bangalore

🔑 MANDATORY SKILLS:

• Amazon EMR

• Python

• Scala

• Data Engineering

📋 KEY REQUIREMENTS:

• 6+ years of relevant experience in Data Engineering.

• Strong hands-on experience with Amazon EMR.

• Strong programming skills in Python and Scala.

• Experience with large-scale data processing and data engineering solutions.

• Strong problem-solving and communication skills.

📩 Interested candidates can share their updated resumes:

📧 pavithra.e @vysystems. com

📞 8 9 2 5 8 0 2 4 5 7

🔄 Know someone who would be a good fit? Tag them or share this post!

#Hiring #DataEngineer #DataEngineering #AmazonEMR #Python #Scala #AWSJobs #BangaloreJobs #ITJobs #TechHiring #HiringNow

Job Summary:

Build scalable full stack applications with AI integrations across Frontend and backend systems in a fast paced product environment. The role focuses on delivering intelligent features for business use.

Job Description:

• Design and develop full stack web applications
• Integrate AI/LLM features into product modules
• Build and consume APIs and manage databases
• Collaborate with product, QA and design teams
• Optimize performance, security and deployment workflows

Must Have

• Should Have working knowledge of Go Lang
• React JS, Python, APIs and database (MySQL) integration
• Should have working exp of agentic tools like Claude, Codex etc.
• Understanding of cloud deployment, version control (GIT) and testing

Desired to have

• Exposure to prompt engineering, vector databases and RAG
• Knowledge of CI/CD, Docker and performance optimization
• LangChain or similar frameworks, data pipelines and monitoring
• Familiarity with AWS/Azure/GCP and security best practices
• Experience integrating AI APIs into business workflows 

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

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

REQUIRED SKILLS — PROGRAMMING & DEVELOPMENT

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

ARTIFICIAL INTELLIGENCE & MACHINE LEARNING

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

TECHNOLOGY STACK

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

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

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

Backend: Python · FastAPI · Flask · REST APIs

Database: MySQL

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

🚀 Job Title : Data Engineer – AWS, PySpark & Airflow

Experience : 5+ Years

Industry : Health Insurance / BFSI

Location : Sector 43, Gurugram, Haryana

Work Mode : Work From Office (5 Days a Week)

Employment Type : Full-Time

Role Overview :

We are looking for an experienced Data Engineer with strong hands-on expertise in AWS Data Engineering, Data Lake Architecture, Python, SQL, PySpark, and Apache Airflow.

The candidate will be responsible for designing, developing, and maintaining scalable, reliable, and high-performance data pipelines using AWS cloud technologies. The role involves building end-to-end ETL / ELT workflows, implementing data transformation and processing solutions, optimizing pipeline performance, and ensuring the reliability of production data systems.

Mandatory Skills :

AWS Data Engineering | Data Lake Architecture | Amazon S3 | AWS Glue | Amazon EMR | Athena | Redshift | Python | SQL | PySpark | Apache Spark | Apache Airflow | ETL/ELT | PostgreSQL | Data Modelling | Pipeline Optimization | Production Support | Root Cause Analysis

Key Responsibilities :

• Design, develop, and maintain end-to-end data pipelines for data ingestion, staging, transformation, curation, and consumption.
• Build and manage AWS-based data lake solutions using Amazon S3, AWS Glue, Amazon EMR, Athena, and Redshift.
• Develop, maintain, and optimize ETL / ELT pipelines using Python, SQL, Apache Spark, and PySpark.
• Implement and manage workflow orchestration using Apache Airflow, including scheduling, dependency management, retries, monitoring, and failure handling.
• Integrate data from multiple structured and semi-structured sources.
• Design and maintain data models, dimensional models, and analytical data marts.
• Work with relational databases, including PostgreSQL and Amazon RDS.
• Optimize Spark jobs, SQL queries, data transformations, and cloud resource utilization.
• Implement data quality checks, validation rules, and error-handling mechanisms.
• Monitor production data pipelines, troubleshoot failures, and perform root cause analysis (RCA).
• Ensure pipeline reliability, scalability, performance, and compliance with service-level agreements (SLAs).
• Follow data security, access management, governance, and sensitive-data protection best practices.
• Collaborate with business, analytics, and application teams to deliver effective data solutions.
• Maintain technical documentation and follow established data engineering standards.

Required Technical Skills :

• AWS Data Engineering : Strong hands-on experience with AWS-based data engineering and data lake architecture.
• AWS Services : Amazon S3, AWS Glue, Glue Data Catalog, Amazon EMR, Athena, Redshift, AWS Lambda, and IAM.
• Programming : Strong proficiency in Python and SQL.
• Big Data Processing : Hands-on experience with Apache Spark and PySpark.
• Workflow Orchestration : Experience developing and managing workflows using Apache Airflow.
• ETL/ELT Development : Experience building scalable data ingestion, transformation, and processing pipelines.
• Database Technologies : Good understanding of relational databases and PostgreSQL concepts.
• Data Modelling : Experience with data modelling, data transformation, and analytical data structures.
• Production Support : Ability to monitor pipelines, troubleshoot failures, perform RCA, and resolve production issues.
• Performance Optimization : Experience optimizing SQL queries, Spark jobs, and data processing workflows.

Good-to-Have Skills :

• Experience with AWS Database Migration Service (DMS) and Amazon RDS.
• Familiarity with dbt for data transformation and modelling.
• Knowledge of Delta Lake, Apache Iceberg, or Apache Hudi.
• Exposure to Apache Kafka and real-time data streaming.
• Familiarity with GraphQL, Hasura, or similar data-serving technologies.
• Understanding of data governance and data quality frameworks.
• Experience in the BFSI, healthcare, or health insurance domain.

Candidate Requirements :

• 5+ years of relevant experience in Data Engineering.
• Proven hands-on experience building and maintaining production-grade data pipelines on AWS.
• Strong understanding of data lake architecture and large-scale data processing.
• Practical experience with Apache Airflow and Spark / PySpark-based transformations.
• Strong programming, analytical, debugging, and problem-solving skills.
• Experience handling production incidents, pipeline failures, and performance bottlenecks.
• Ability to take ownership of deliverables and work effectively with cross-functional teams.
• Good communication, collaboration, and technical documentation skills.
• Willingness to work from the Gurugram office five days a week.

Ideal Candidate :

The ideal candidate is a hands-on Data Engineer who can independently build, optimize, and maintain AWS-based data pipelines, work with large datasets using PySpark, orchestrate workflows through Airflow, and resolve production issues in a business-critical environment.

We are hiring experienced Data Engineers for a permanent opportunity in Bangalore.

Job Description

Role: Data Engineer

Location: Bangalore

Experience: 6+ Years

Key Responsibilities:

• Design, develop, and maintain scalable data processing pipelines using Amazon EMR.
• Develop data engineering solutions using Python and Scala.
• Process and transform large volumes of structured and unstructured data.
• Build and optimize distributed data processing workflows for performance and scalability.
• Work with big data technologies and cloud-based data processing environments.
• Perform data integration, validation, transformation, and quality checks.
• Troubleshoot data pipeline issues and optimize processing performance.
• Collaborate with data architects, analysts, and development teams to deliver reliable data solutions.

Required Skills:

• Strong hands-on experience with Amazon EMR.
• Proficiency in Python and Scala.
• Experience in big data processing and data pipeline development.
• Good understanding of distributed computing and data transformation techniques.
• Experience in performance tuning and troubleshooting data processing jobs.
• Strong analytical, problem-solving, and communication skills.

Java, Spring Boot, Angular, Python

Java python Angular - 4 to 7 yrs (Bangalore)

interested candidate: 6 3 8 5 0 7 6 1 4 2

Email: revathi.r @ vysystems. com

Share the CV in WhatsApp or email

• Business: Immerse in operations until you think like an insider.Rapidly acquire domain expertise through direct observation, translate between business and engineering seamlessly, and mentor engineers in your area on immersion. Influence senior stakeholders effectively, manage complex stakeholder landscapes with competing agendas, and build trust rapidly with new stakeholders.
• Delivery: Lead rapid delivery initiatives across teams in your area, coach on prototype-first approaches, and establish trust through consistent fast delivery. Build complete applications rapidly across any technology stack, select the right tools for each problem, and define clear criteria for prototype-to-production transitions.
• Generative AI: Architect RAG systems for complex use cases across teams, implement advanced techniques (hybrid search, reranking, query expansion), mentor engineers on RAG best practices, and establish RAG standards. Lead evaluation strategy across teams, establishing annotation guidelines, training human-calibrated LLM judges, and building evaluation pipelines that connect tracing to datasets to experiments.
• People: Build high-performing teams across your area, navigate complex interpersonal dynamics, foster psychological safety, and create environments where diverse perspectives are valued. Influence through communication at all levels — from frontline to executive. Handle difficult conversations skilfully and train engineers in your area on effective communication.
• AI-Augmented Development: Optimise AI tool usage across teams in your area, train engineers on AI-augmented and agentic engineering workflows, evaluate new AI development tools, and establish practices that balance AI speed with verification rigour.
• Scale:  Design  complex  multi-component systems  end-to-end,  evaluate architectural options for large initiatives across teams, guide technical decisions or your area, and mentor engineers on architecture. Create debt reduction strategies across teams, influence roadmap decisions to include debt work, and teach engineers when to accept debt for speed versus when to invest in quality.

What You Bring

• Bachelor’s degree in computer science, Software Engineering, or related field with 7+ years of relevant professional experience.
• Deep production experience with Python and JavaScript/TypeScript across backend and frontend, with demonstrated ability to work comfortably across the full stack.
• Strong experience with modern frontend frameworks (such as Next.js or React) and backend API development.
• Extensive experience with cloud platforms (AWS preferred; Azure or GCP also valued), including infrastructure-as-code tools (such as CloudFormation or Terraform).
• Deep Working knowledge of multiple database paradigms, including relational databases (such as PostgreSQL), document databases, and key-value stores (such as Redis), with the ability to select the right storage technology for each problem.
• Strong experience with CI/CD pipelines (such as GitHub Actions), containerisation, and production deployment strategies.
• Demonstrable fluency with AI coding tools (such as Claude Code, Cursor, GitHub Copilot, or similar) and proven ability to design agentic engineering workflows and train teams on AI-augmented development practices.
• Hands-on experience architecting production generative AI applications (LLM integrations, vector databases, RAG systems, evaluation pipelines) is essential.
• Experience leading technical initiatives across multiple teams, mentoring engineers, and establishing engineering practices is required.
• Experience navigating ambiguous problem spaces, working directly with business stakeholders and end users, and shipping working solutions rapidly is required.
• Experience in an embedded, forward-deployed, or consulting-style engineering model is a strong plus.

• Must have exceptional communication skills and demonstrated ability to influence at senior levels. This role requires comfort leading across ambiguous environments, building trust-based relationships with commercial stakeholders at all levels, developing junior and mid-level engineers, and making strategic decisions that balance delivery speed with architectural integrity. You will shape engineering practices across your area and be expected to lead multi-team initiatives.

About the role

We are hiring a Principal Engineer to own the hardest technical problems in our product and see them through from first sketch to stable production. You will set technical direction, design systems that scale, and raise the engineering bar through your own work and the people around you. This is a hands-on leadership role: you write code, review designs, and ship.

What will you do?

You will own outcomes, not just tasks. Expect to spend your time on the following.

• Own projects end to end. Take an ambiguous problem, shape the requirements, design the solution, break down the work, deliver it to production, and stay accountable for how it runs afterwards.

• Lead system design. Author and review architecture for services, data pipelines and integrations, with clear trade-offs on scale, latency, cost, consistency and reliability.

• Write and review critical code. Build the hardest components yourself, and set standards for code quality, testing and maintainability through code and design reviews.

• Own deployment and operations. Design CI/CD, infrastructure and release strategies. Drive observability, on-call readiness, incident response and post-incident learning.

• Solve hard problems. Debug production issues across the stack, and find root causes in performance, concurrency, data and scaling problems.

• Mentor and multiply. Coach senior and junior engineers, grow future tech leads, and make the whole team faster and more confident.

• Partner across functions. Work with product, design, data and business teams to turn goals into technical plans, and to say no or reshape scope when needed.

• Shape technical strategy. Guide build-versus-buy decisions, manage tech debt, evaluate new technologies, and contribute to the engineering roadmap.

• Raise the bar. Help define engineering practices, hiring standards and culture, and take part in interviewing.

What are we looking for?

• Bachelor's degree in Computer Science or a related field, or equivalent practical experience.

Core engineering

• 10+ years of professional software engineering, with a track record of shipping and running production systems.

• Strong computer science fundamentals: data structures, algorithms and complexity, operating systems, networking, databases and concurrency.

• Fluency in at least one major backend language (for example Python, Go, Java, or Node.js/ TypeScript) and the ability to pick up others quickly.

• Deep knowledge of relational and NoSQL data stores: schema design, indexing, transactions, query tuning and replication.

System design and problem solving

• Proven ability to design distributed systems that are scalable, fault tolerant and cost aware, and to explain the trade-offs clearly.

• Experience with APIs, event-driven and asynchronous architectures, queues, caching and service-to-service communication.

• A structured approach to ambiguous problems: break them down, test assumptions, decide with incomplete data, and measure results.

• Strong debugging instincts, including performance profiling and production troubleshooting.

Delivery and operations

• Have led at least two significant projects from inception to production, including planning, milestones, risk management and launch.

• Hands-on experience with deployment: CI/CD pipelines, containers (Docker, Kubernetes), a major cloud (AWS, GCP or Azure), and infrastructure as code.

• Practical experience with monitoring, logging, alerting, SLOs and incident management.

• Habit of writing tests and automation, and of leaving systems more reliable than you found them.

Leadership and communication

• Experience leading engineers without formal authority, through influence, mentoring and clear technical writing.

• Excellent written and verbal communication: design docs, RFCs and concise updates to non-technical stakeholders.

• Ownership mindset, sound judgment on priorities, and comfort working in a fast-moving environment.

Nice to have

• Experience in fintech, lending or another regulated, data-heavy domain.

• Exposure to AI/ML or LLM-based systems in production: model serving, evaluation, retrieval, and cost and latency management.

• Deep experience with data engineering: streaming, batch pipelines, warehouses or search systems.

• Security and compliance awareness: authentication, encryption, audit trails, secure SDLC.

• Experience with multi-tenant SaaS, high-throughput systems or zero downtime migrations.

• Open-source contributions, conference talks, or technical writing.

• Experience scaling an engineering team or helping set up hiring and onboarding practices.

Job Description – Java + Python + Angular Developer

Job Title: Java + Python + Angular Developer

Experience: 4–7 Years

Location: Bangalore

CTC: 26–30 LPA

Mandatory Skills

• Java
• Spring Boot
• Angular
• Python

Roles & Responsibilities

• Design, develop, and maintain scalable applications using Java and Spring Boot.
• Develop robust backend services and REST APIs using Java.
• Build responsive and reusable frontend applications using Angular.
• Develop Python-based applications, scripts, and automation solutions as required.
• Integrate frontend and backend services through REST APIs.
• Troubleshoot, debug, and optimize application performance.
• Write clean, maintainable, and reusable code following development best practices.
• Participate in code reviews, testing, and application deployment activities.
• Collaborate with cross-functional teams to understand requirements and deliver quality solutions.
• Ensure applications are scalable, secure, and reliable.

Candidate Requirements

• 4–7 years of relevant software development experience.
• Strong hands-on experience in Java and Spring Boot.
• Good experience with Angular for frontend development.
• Strong programming experience in Python.
• Good understanding of REST APIs and full-stack application development.
• Strong problem-solving and communication skills.
• Candidates should be willing to work from Bangalore.

INTERESTED CANDIDATE SHARE RESUME TO BELOW WHATSAPP OR EMAIL

AEM Developer

Mandatory Skills – AEM Developer Integration is must

AEM, AEM Basics, AEM Integration,Sling Model Servlets,Slingjobs,Schedulers, Workflows, AEM APi, OSGI, Java

location : Bangalore

exp: 5- 7

Notice Period:- Immediate joiners or 15 days

WhatsApp or call: 6 3 8 5 0 7 6 1 4 2

email: revathi.r @ vysystems . com

Job Description:

We are looking for an experienced Production Support Engineer to support our Internet Banking Application. The candidate will be responsible for application production support, release deployments, middleware operations, monitoring, and incident management to ensure high availability, stability, and performance of banking applications.

Responsibilities:

• Provide production support for Internet Banking Applications and ensure high availability.
• Manage release deployments and middleware operations in coordination with development and operations teams.
• Monitor application performance using Splunk, AppDynamics, and Grafana.
• Handle incident management, troubleshooting, root cause analysis, and timely issue resolution.
• Support OS patching and routine system maintenance activities.
• Collaborate with cross-functional teams to improve application stability and performance.
• Maintain technical documentation, troubleshooting procedures, and support processes.
• Participate in on-call support rotations as required.

Mandatory Skills:

• Application Production Support experience in banking or financial services.
• Strong knowledge of middleware technologies and operations.
• Hands-on experience with Splunk, AppDynamics, and Grafana.
• Good understanding of incident management and troubleshooting.
• Knowledge of OS patching and system maintenance.

Preferred Skills:

• Cloud infrastructure and operations experience.
• Scripting knowledge in Python or Bash.
• Understanding of ITIL processes and best practices.
• Strong analytical, problem-solving, communication, and collaboration skills.

roll: UiPath RPA Developer

skill: UiPath , Orchestrator , RE Framework , Dispatcher–Performer Framework , Document Understanding, Python /VB.NET/.NET

exp: 6 - 10 Years

location : Bangalore

Notice Period:- Immediate joiners or 15 days

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

interested candidate kindly text to this WhatsApp number

Job Summary:

We are looking for an experienced Java Application Production Support Engineer / Java SRE with strong expertise in application support, Unix, Oracle, and OpenShift. The candidate will be responsible for production monitoring, troubleshooting, performance optimization, and automation to ensure high availability and stability.

Mandatory Skills:

• Java Application Production Support / SRE
• Unix/Linux and Oracle Database
• OpenShift (OCP)
• SQL
• Splunk and AppDynamics
• Autosys
• Python scripting
• Grafana monitoring and dashboards

Responsibilities:

• Handle production incidents, troubleshooting, and root cause analysis.
• Monitor application performance using Splunk, AppDynamics, and Grafana.
• Support Java applications deployed on OpenShift.
• Manage SQL queries, batch jobs, and automation scripts.
• Collaborate with teams to improve system reliability and availability.

Experience: 8+ years (including 5+ years hands-on with Apache Kafka platform engineering)

Key Responsibilities

• Manage Kafka cluster lifecycle: provisioning, configuration tuning, upgrades, and decommissioning

• Deploy, operate, and maintain Kafka on Kubernetes using Confluent for Kubernetes (CFK)

• Monitor cluster health and set up alerting across consumer lag, broker health, and topic throughput

• Design and operate disaster recovery and multi-region replication strategies

• Enforce Kafka security policies including access reviews and ACL management

• Troubleshoot performance bottlenecks, consumer lag issues, and broker failures

Must Have

• 8+ years in messaging/streaming platform engineering, with 5+ years on Apache Kafka platform engineering

• Hands-on administration of self-managed on-premises Kafka clusters in KRaft mode

• Confluent for Kubernetes (CFK): operator management and custom resource configuration

• Kafka Connect: connector lifecycle, SMTs, and error handling

• Confluent Schema Registry; schema evolution and compatibility modes

• Kafka security: TLS/mTLS, SASL, and ACL configuration and troubleshooting

• Proficiency in Java or Scala; Python for scripting and tooling

• Observability: Prometheus, Grafana, and OpenTelemetry

Good to Have

• Apache Flink for complex event processing beyond Kafka Streams

• CDC pipelines into Kafka

• Operational experience with MirrorMaker 2 or Confluent Replicator in multi-DC setups

• Knowledge of event-driven architecture or data mesh principles

• Build and maintain infrastructure-as-code for Kafka resources

• Integrate Kafka platform changes with CI/CD pipelines for topic and schema deployments

Position Details

| **Experience** | 5–8 Years |

| **Work Location** | Mumbai Suburbs-Andheri |

| **Start Date** | Immediate |

| **CTC** | Open to Discussion |

## Job Description

The selected candidate will be responsible for leading backend development, managing cloud infrastructure and deployments, designing scalable system architectures, and mentoring the engineering team. The role requires strong technical expertise, leadership capabilities, and the ability to translate business requirements into effective technical solutions.

### 1. DevOps and Cloud Infrastructure

- Create and configure cloud instances on Azure, AWS, or GCP.

- Deploy applications and programs to cloud servers and DevOps environments.

- Ensure deployment stability, system uptime, and performance monitoring.

- Automate deployment pipelines and continuously improve CI/CD practices.

- Implement and maintain reliable, scalable, and secure deployment processes.

### 2. Architecture and Backend Development

- Design system architectures with a focus on performance, security, scalability, and reliability.

- Design, develop, and maintain clean, scalable, and optimized backend applications, preferably using Node.js.

- Troubleshoot and resolve complex technical issues across development, testing, and production environments.

- Translate business requirements into effective technical solutions and ensure timely delivery.

- Develop and maintain APIs, microservices, databases, and system integrations.

### 3. Team Leadership and Management

- Lead, mentor, and guide a team of backend developers and engineers.

- Drive Agile development processes, including sprint planning, daily stand-ups, and retrospectives.

- Conduct code reviews and ensure adherence to coding standards and engineering best practices.

- Promote collaboration, accountability, and a high-performance engineering culture.

- Support team members in resolving technical challenges and improving their skills.

## 4.Skills and Qualifications Required

- B.Tech / B.E. in Computer Science, Information Technology, or a related field.

- Strong proficiency in backend development using Node.js, JavaScript, Python, or Java.

- Hands-on experience with DevOps practices and cloud deployment environments.

- Solid understanding of APIs, microservices, databases, and system integration.

- Experience in leading development teams within an Agile/Scrum environment.

- Working knowledge of Linux, Kafka, and Docker.

- Good understanding of CI/CD pipelines, cloud technologies, and deployment automation.

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

##5. Behavioural Competencies

- **Team Leadership:** Ability to manage, train, mentor, and guide team members.

- **Relationship Management:** Strong interpersonal skills and the ability to build effective working relationships.

- **Analytical Thinking and Innovation:** Strong analytical capabilities, with a focus on innovative problem-solving.

- **Business Acumen:** Ability to understand business use cases and translate them into practical technical solutions.

- **Customer Empathy:** Ability to understand customer needs and deliver solutions that enhance customer experience.

- **Communication:** Excellent verbal and written communication skills.

Salary will be decided based on your skills and experience.

{ contact No: 8 9 2 5 8 0 2 4 5 7 } , pavithra.e @vysystems. com

Job Description – Java Full Stack + DevOps Developer

Job Title: Java Full Stack + DevOps Developer

Experience: 8+ Years

Location: Bangalore / Hyderabad

CTC: Up to 30 LPA

Notice Period: Immediate to 20 Days

Mandatory Skills

• Java
• Java Full Stack Development
• Angular or React
• Python
• DevOps
• CI/CD

Roles & Responsibilities

• Design, develop, and maintain scalable Java Full Stack applications.
• Develop robust backend services using Java and related frameworks.
• Build responsive and reusable frontend applications using Angular or React.
• Develop and integrate REST APIs between frontend and backend systems.
• Use Python for automation, scripting, and application support as required.
• Implement and maintain DevOps practices across the application lifecycle.
• Design, configure, and maintain CI/CD pipelines for automated build, deployment, and release processes.
• Collaborate with development, QA, DevOps, and other cross-functional teams.
• Troubleshoot application and deployment issues and optimize system performance.
• Follow coding standards, security practices, and software development best practices.
• Participate in code reviews and provide technical guidance to team members.

Candidate Profile

• 8+ years of strong experience in Java Full Stack Development.
• Strong hands-on experience with Java and Angular or React.
• Good working knowledge of Python.
• Strong understanding of DevOps and CI/CD practices.
• Experience working across development, deployment, and automation activities.
• Strong problem-solving and communication skills.
• Candidates available to join immediately to 20 days are preferred.

We’re Hiring: Java & Angular Developer with Python & LLM

📍 Location: Bangalore

💼 Experience: 4–6 Years

🕒 Employment Type: Full-time

We are looking for a skilled Full Stack Developer with strong experience in Java backend development and Angular frontend development, along with Python knowledge for API and LLM integration.

Mandatory Skills:

• Java
• Microservices
• Spring Boot
• Angular
• Python

Role & Responsibilities:

Develop and maintain scalable enterprise applications using Java, Spring Boot, and Microservices. Build responsive web applications using Angular and TypeScript. Design and integrate REST APIs, and use Python to connect applications with external APIs and LLM-based services.

Work closely with cross-functional teams to deliver secure, high-quality applications while following coding standards, testing practices, and Agile methodologies.

Preferred Skills: REST APIs, SQL/DB2, Kafka or MQ, Git, CI/CD, Cloud platforms, and exposure to LLM, GenAI, or RAG-based applications.

📩 Interested candidates can share their updated resumes or refer suitable profiles.

#Hiring #JavaDeveloper #SpringBoot #Microservices #AngularDeveloper #Python #FullStackDeveloper #LLM

Strong Data Analyst Profile with Python, SQL, and data-pipeline expertise, ideally with retail / e-commerce datasets

2

Mandatory (Experience 1): Must have 4+ years of hands-on data-analyst experience, working with large datasets across areas such as sales, inventory, pricing, promotions, and customer behaviour.

3

Mandatory (Tech skill 1): Must have strong hands-on Python for data processing, transformation, automation, and analysis

4

Mandatory (Tech skill 2): Must have strong SQL skills, including complex queries, joins, aggregations, and data validation.

5

Mandatory (Tech skill 3): Must have a solid understanding of Data Lake architecture, ingestion, storage, and processing workflows

6

Mandatory (Tech skill 4): Must have hands-on experience with ETL / ELT pipelines, data integration, and transformation

7

Mandatory (Tech skill 5): Must have experience with Azure or GCP data services.

8

Mandatory (Tech skill 6): Must have understanding of or experience with Databricks and distributed data processing.

9

Mandatory (Tech skill 7): Must have knowledge of data modeling, data warehousing, and Lakehouse architecture

10

Mandatory (Tech skill 8): Must have experience with Power BI, Tableau, or Excel for reporting.

11

Mandatory (Communication): Must have strong analytical, documentation, and stakeholder-communication skills.

12

Mandatory (Education): Must hold a Bachelor’s degree in Computer Science, IT, Engineering, or a related field.

13

Mandatory (Note1): This is a 6-month contract role. Candidate must be comfortable with the contract engagement and able to join immediately (urgent — onboarding within ~a week)

Applied AI Engineer

About the Role

We are building an AI-powered platform that transforms credit origination by automating manual processes and enabling lenders to underwrite more loans with greater accuracy and lower risk.

We are looking for an experienced Applied AI Engineer to design and build production-grade Agentic AI systems capable of complex, multi-step reasoning across financial data, legal documents, and other unstructured information.

As an early engineering team member, you will take ownership of core AI architecture, multi-agent orchestration, reasoning workflows, evaluation frameworks, and scalable AI infrastructure.

Key Responsibilities

• Design and develop stateful, multi-agent AI systems for complex reasoning and decision-making.
• Build and optimize LLM pipelines using frameworks such as LangChain, DSPy, and GEPA.
• Implement RAG, prompt optimization, memory management, tool integration, and human-in-the-loop workflows.
• Develop AI evaluation frameworks using LLM-as-a-Judge and scenario-based testing.
• Implement AI observability and monitoring to track accuracy, latency, cost, and system performance.
• Build ETL pipelines and work with structured and unstructured data, SQL/NoSQL databases, vector databases, and graph-based data models.
• Integrate external tools and systems using modern agent protocols such as Model Context Protocol (MCP).
• Deploy and maintain AI services on AWS or Azure.
• Implement CI/CD pipelines, containerization, and Infrastructure as Code for reliable production deployments.

Required Qualifications

• 5+ years of professional software development experience in Python or JavaScript.
• Proven experience building and deploying production-level Agentic AI systems or complex LLM reasoning applications.
• Hands-on experience with LangChain and LLMOps, including tools such as Langfuse, Weights & Biases (W&B), or Helicone.
• Strong understanding of LLMs, RAG, prompt engineering, multi-agent orchestration, memory management, and tool calling.
• Experience with DSPy, GEPA, or advanced LLM inference and optimization techniques.
• Strong data engineering fundamentals, including ETL, SQL/NoSQL databases, and vector databases.
• Familiarity with MCP and human-in-the-loop workflows.
• Experience with AWS or Azure and modern DevOps practices, including Docker, CI/CD, and Infrastructure as Code.

Good to Have

• Experience with RLHF or RLAIF.
• Knowledge of model fine-tuning techniques such as LoRA and QLoRA.
• Experience with graph databases and graph-based data models.
• Exposure to financial services, credit underwriting, risk analysis, or document-intensive AI applications.

Why Join Us?

• Work on advanced Agentic AI and complex reasoning systems beyond conventional chatbot applications.
• Build foundational AI architecture and production-grade LLM workflows.
• Take ownership of technical decisions and system design as an early engineering team member.
• Solve challenging problems at the intersection of AI, finance, and intelligent automation.

Full Stack Engineer

About the Company

We are building an AI-powered platform that transforms credit origination by automating manual bottlenecks and enabling lenders to process more loans with greater accuracy and lower risk. Our mission is to revolutionize the $3 trillion+ asset-based finance market through advanced AI technology, deep industry expertise, and strategic partnerships.

The Opportunity

Join us at an exciting stage of growth as we build and scale an enterprise-grade financial technology platform. As a Full Stack Engineer, you will play a key role in developing core platform features, including a proprietary decisioning system, robust data security for AI applications, and advanced document-processing tools.

Your work will help automate document verification, data extraction, and decision-support workflows. You will collaborate with experienced engineers in a fast-paced, product-focused environment, working with technologies such as Node.js, PostgreSQL, Python, and React.

This is an opportunity to contribute to a high-growth startup, solve real-world financial challenges, and build scalable AI-powered solutions.

Key Responsibilities

1. Full Stack Development

• Design, develop, and maintain full-stack web applications using Node.js, Python, PostgreSQL, GraphQL, and React.
• Build scalable, reliable, and maintainable application features.
• Develop responsive and efficient user interfaces integrated with robust backend services.

2. AI and Document Processing

• Build Python-based AI pipelines to automate document processing and underwriting workflows.
• Contribute to document verification, data extraction, and decision-support capabilities.
• Support the integration of AI-powered features into the core platform.

3. Collaboration and Product Development

• Collaborate with product and engineering teams to translate user requirements into scalable and efficient code.
• Participate in technical discussions and contribute to feature planning and implementation.
• Work closely with team members to deliver high-quality product features.

4. Performance and Scalability

• Optimize application performance and ensure efficient data flow and real-time functionality.
• Identify and resolve technical issues across the application stack.
• Contribute to architectural decisions that support platform scalability and long-term growth.

5. Code Quality and Deployment

• Participate in code reviews, testing, debugging, and deployment.
• Follow software development best practices to ensure code quality, reliability, and maintainability.
• Contribute to CI/CD pipelines and application deployment processes.

Required Qualifications

• 3+ years of professional experience as a Full Stack Engineer.
• Strong proficiency in Node.js and PostgreSQL, with experience in Python and hands-on experience with React.
• Experience developing and maintain

GCP Data engineer

Exp 9+yrs

Bangalore/Hyderabad

Lead exp+ Python + pyspark + sql or plsql

immediate to 15days joiners

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

Job Title : Full-Stack AI Product Engineer

Experience : 3+ Years

Work Mode : Remote

Time Zone : IST

Engagement Type : Freelance

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

Role Overview :

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

Mandatory Skills :

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

Key Responsibilities :

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

Required Skills :

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

Preferred Qualifications :

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

Important Requirements :

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

About the company

We are an AI diffusion company. We partner with midmarket companies in asset-heavy, regulated industries to co-build deeply industry-specific agentic and machine learning solutions, which then get diffused across the industry through revenue-share and equity-linked models.

Our Past

We have built and sold two companies, one of which was an AI company. Our founders and leaders are Math PhDs, Ivy League University Alumni, Ex-Googlers, and successful entrepreneurs.

Team

Our team of 20+ employees consists of data scientists, AI/ML Engineers, and mathematicians from top engineering and research institutes such as IITs, CERN, IISc, UZH. Our team includes academicians, IBM Research Fellows, and former founders. This role focuses on healthcare and RCM, working alongside our AI/ML engineers, data scientists and domain specialists.

Key Responsibilities

• Lead product ideation, solution design, and technical strategy from concept to execution.
• Drive end-to-end product development, translating business needs into scalable technical solutions.
• Build and lead engineering teams to deliver high-impact products.
• Design and develop robust data systems to process and structure unorganized data from ERP/CRM platforms.
• Leverage AI and domain expertise in healthcare/RCM to build innovative solutions.
• Drive technology-led growth, with a focus on product scalability and business outcomes.

\Required Skills & Experience

• 15–20 years of experience in technology leadership, preferably as a CTO or senior technology leader.
• Proven experience building and/ or exiting startups.
• Strong expertise in data engineering, complex data systems, and unstructured data processing.
• Experience with AI-driven products, preferably in healthcare or Revenue Cycle Management (RCM).
• Strong product thinking, system design, architecture, and end-to-end execution capabilities.
• Ability to translate business requirements into technical roadmaps and scalable products.

What you need • • • • • • Delivered inside a regulated environment: code review, change control, a real audit trail. Based in, or able to relocate to, Bengaluru or Mumbai for the engagement. 7–15 years building production software, with .NET (C#, ASP.NET Core) as your primary stack. Python you have shipped and maintained — services, pipelines or AI components other people depend on, not occasional scripting. Hands-on work with LLMs in production: retrieval-augmented generation, prompt and agent design, and a clear account of how you evaluated whether it worked. Comfortable across SQL, REST and asynchronous integration patterns, on Azure or AWS, with CI/CD, containers and infrastructure as code. Good to have • • Migration work from .NET Framework to modern .NET. Azure OpenAI, Semantic Kernel, LangChain or LlamaIndex. • • Snowflake, including Cortex. Real estate, lease management or corporate services domain exposure

About the company

We are an AI diffusion company. We partner with midmarket companies in asset-heavy, regulated industries to co-build deeply industry-specific agentic and machine learning solutions, which then get diffused across the industry through revenue-share and equity-linked models.

Our Past

We have built and sold two companies, one of which was an AI company. Our founders and leaders are Math PhDs, Ivy League University Alumni, Ex-Googlers, and successful entrepreneurs.

Team

Our team of 20+ employees consists of data scientists, AI/ML Engineers, and mathematicians from top engineering and research institutes such as IITs, CERN, IISc, UZH. Our team includes academicians, IBM Research Fellows, and former founders. This role focuses on healthcare and RCM, working alongside our AI/ML engineers, data scientists and domain specialists.

Work you’ll do

We are looking for an experienced Project Manager cum Lead to own product decisions and project delivery for our healthcare AI pod. You will lead engineers building AI agents, automations and data workflows for healthcare revenue cycle management, while remaining hands-on in solution design, code reviews, prototyping and technical problem-solving.

You will work directly with client CXOs, billing leaders and operations teams to identify problems, agree measurable outcomes and decide what to build first.

You will translate those decisions into a practical roadmap, manage delivery and remain accountable for adoption and performance in production.

The work includes payer-portal automation, claim status and document retrieval, voice-based payer follow-up, analysis of revenue-cycle bottlenecks and AI-assisted practice insights.

Responsibilities

• Lead the healthcare AI pod, setting technical direction, reviewing engineering work, mentoring engineers and resolving delivery blockers.
• Work with client CXOs and operational leaders to define business problems, establish baselines and agree measurable outcomes.
• Own product discovery and prioritization, translating user needs into a roadmap, requirements and clear acceptance criteria.
• Make solution and build-versus-buy decisions, choosing between APIs, rules-based automation, RPA and AI based on reliability, cost and business value.
• Stay hands-on through architecture and code reviews, targeted prototypes and troubleshooting of complex production issues.
• Own project scope, estimates, milestones, resources and dependencies. Manage changes and explain their impact on cost, timelines and outcomes.
• Lead executive reviews, communicate progress and risks clearly, and secure decisions needed to keep delivery moving.
• Establish evaluation, security and release criteria, including monitoring, exception handling and human escalation.
• Work with billing and operations teams through rollout, adoption and ongoing improvement, measuring results against agreed baselines.
• Identify capabilities that can be reused across engagements and incorporate them into the product roadmap.

Who you are

You are an engineering leader who remains close to the code and takes responsibility for what the team delivers. You can investigate a technical issue with an engineer, make a product prioritization decision with an operations leader and explain the trade-offs to a client executive. You bring structure to unclear problems, make decisions with incomplete information and know when to challenge a request or change direction. You balance delivery speed with reliability, security and maintainability, and support your decisions with evidence. You have led teams through production delivery, handled difficult stakeholder conversations and stayed accountable for adoption and business outcomes after launch.

Skills & Requirements

Must have

• At least 7 years of relevant engineering and technical leadership experience, with recent hands-on involvement in solution design, code reviews, prototyping and production troubleshooting.
• Experience leading engineering teams delivering AI or automation systems into live operations, with accountability for technical quality, delivery and business outcomes.
• Experience deploying and supporting LLM-based applications or AI agents, including retrieval, tool calling, evaluation, error handling and human escalation.
• Strong Python and SQL skills, with the ability to review code, assess API and data integrations, and guide browser or workflow automation using tools such as Playwright, Selenium or UiPath.
• Experience delivering applications on at least one cloud platform—AWS, Azure or GCP—with an understanding of containers, deployment pipelines, monitoring and operating costs.
• Experience making product decisions, including discovering user needs, prioritizing workflows, defining acceptance criteria and balancing client-specific requirements against reusable capabilities.
• Experience managing client engagements from discovery through deployment and adoption, including scope, estimates, resource planning, dependencies and recovery of projects that have gone off track.
• Experience working directly with CXOs and senior operational leaders to agree outcomes, explain trade-offs, resolve conflicting priorities and manage expectations.
• Experience delivering healthcare or RCM solutions, with practical understanding of billing workflows, data quality issues and operational exceptions.
• Experience handling sensitive healthcare data and incorporating access controls, secure logging and approved data-handling practices into delivery.
• Ability to demonstrate your own technical contribution, a significant product decision and measurable outcomes from an engagement you led.

Preferred experience

• Experience delivering solutions for US healthcare providers or RCM companies, including working with US billing teams and payer workflows.
• Experience with practice-management or EHR integrations, payer portals, EOB/ERA data or analysis of revenue-cycle performance.
• Experience turning capabilities developed for individual clients into reusable products.
• Experience hiring and developing engineering teams.
• Experience managing delivery budgets, engagement profitability or a practice P&L.

Working with us

We are a young company, but we believe strongly in thinking long-term, while acting with urgency. Our ethos is rooted in innovation, efficiency and high-quality outcomes. We believe the future of work is AI-augmented and boundaryless.

Here are some of our guiding principles:

• Think in decades. Act in hours. As an independent company, our moat is time. While our decisions are for the long-term horizon, our execution will be fast – measured in hours and days, not weeks and months.
• Own the canvas. Throw yourself in to build, fix or improve – anything that isn’t done right, irrespective of who did it. Be selfish about improving across the organization – because once the rot sets in, we waste years in surgery and recovery.
• Use data or don’t use data. Use data where you ought to but not as a ‘cover-my-back’ political tool. Be capable of making decisions with partial or limited data. Get better at intuition and pattern-matching. Whichever way you go, be mostly right about it.
• Avoid work about work. Process creeps on purpose, unless we constantly question it. We are deliberate about committing to rituals that take time away from the actual work. We truly believe that a meeting that could be an email, should be an email and you don’t need a person with the highest title to say that out loud.
• High revenue per person. We work backwards from this metric. Our default is to automate instead of hiring. We multi-skill our people to own more outcomes than hiring someone who has less to do. We don’t like squatting and hoarding that comes in the form of hiring for growth. High revenue per person comes from high quality work from everyone. We demand it.