AI/ML Engineer - GenAI, Lang Graph, Azure ML, Databricks

Tata Consultancy Services; Bengaluru; On-site; INR 4,000,000 - 6,000,000; Full time

Job summary

Tata Consultancy Services seeks an experienced AI/ML professional to design, develop, and deploy AI-powered applications using LLMs and Generative AI frameworks. You will build AI agents for workflow automation, optimize RAG solutions, and integrate LLMs across scalable business applications.

Responsibilities include deploying models on Azure ML and Databricks, building APIs, and implementing MLOps with CI/CD.

Qualifications

• 6-8 years of experience in Artificial Intelligence, Machine Learning, or Data Science with hands-on development.
• Minimum 1+ year of Generative AI applications and working with LLMs in enterprise environments.
• Strong experience in LangGraph, CrewAI, AutoGen, or PydanticAI for AI agent development and orchestration.
• Hands-on expertise in RAG, Prompt Engineering, Vector Databases, and LLM Workflows.
• Proficient in Python with strong coding and debugging skills.
• Experience with Azure Machine Learning, Databricks, and cloud deployments.
• Strong knowledge of MLOps/LLMOps, versioning, monitoring, and CI/CD pipelines.
• Experience developing and integrating REST APIs, WebSockets, and Event-Driven Architectures.
• Familiarity with Git, Jenkins, Jira, Confluence, SDLC, and Agile methodologies.
• Experience using AI-assisted tools such as GitHub Copilot, Windsurf, or Codeium.
• Good understanding of enterprise security, governance, compliance, and AI best practices.
• Excellent communication and stakeholder management skills.

Responsibilities

• Design, develop, and deploy AI-powered applications using LLMs and generative AI frameworks.
• Build AI agents for workflow automation and decision-making.
• Develop and optimize RAG solutions and prompt engineering strategies.
• Integrate LLMs like GPT, Claude, and Llama into scalable apps.
• Deploy and manage AI/ML models using Azure ML and Databricks.
• Build REST APIs, WebSockets, and event-driven architectures for real-time services.
• Implement MLOps practices including versioning, monitoring, and CI/CD.
• Collaborate with cross-functional teams to ensure secure, scalable AI in production.
• Write high-quality Python code following SDLC and Agile practices.
• Utilize Git, Jenkins, Jira, Confluence to improve productivity and quality.
• Monitor model performance, troubleshoot production issues, and enhance AI effectiveness.
• Contribute to enterprise AI governance, security, and lifecycle best practices.

Skills

Artificial Intelligence

Machine Learning

Data Science

Generative AI

LLMs

Python

Azure ML

Databricks

MLOps/LLMOps

REST APIs

WebSockets

CI/CD

Git

Jira

Confluence

SDLC

Agile

GitHub Copilot

Windsurf

Codeium

Tools

LangGraph

CrewAI

AutoGen

PydanticAI

Azure Machine Learning

Databricks

GitHub Copilot

Windsurf

Codeium

Job description

Role & responsibilities

• Design, develop, and deploy AI-powered applications using Large Language Models (LLMs) and Generative AI frameworks.
• Build AI agents using LangGraph, AutoGen, CrewAI, or PydanticAI for workflow automation and intelligent decision-making.
• Develop and optimize Retrieval-Augmented Generation (RAG) solutions and prompt engineering strategies for enterprise use cases.
• Integrate LLMs such as GPT, Claude, and Llama into scalable business applications.
• Deploy and manage AI/ML models using Azure Machine Learning and Databricks platforms.
• Build and maintain REST APIs, Web Sockets, and event-driven architectures for real-time AI services.
• Implement ML Ops best practices, including model versioning, monitoring, CI/CD pipelines, and automated deployments.
• Collaborate with cross-functional teams to ensure secure, scalable, and reliable AI solutions in production environments.
• Write high-quality Python code and follow modern software development practices, SDLC processes, and Agile methodologies.
• Utilize development tools such as Git, Jenkins, Jira, Confluence, and AI-assisted coding tools to improve productivity and software quality.
• Monitor model performance, troubleshoot production issues, and continuously enhance AI solution effectiveness.
• Contribute to enterprise AI governance, security, compliance, and best practices for AI system lifecycle management.

Preferred candidate profile

• 6-8 years of experience in Artificial Intelligence, Machine Learning, or Data Science with strong hands-on development expertise.
• Minimum 1+ year of experience building Generative AI applications and working with LLMs in enterprise environments.
• Strong experience in LangGraph, CrewAI, AutoGen, or PydanticAI for AI agent development and orchestration.
• Hands-on expertise in RAG (Retrieval Augmented Generation), Prompt Engineering, Vector Databases, and LLM Workflows.
• Proficient in Python with strong coding, debugging, and software engineering practices.
• Experience with Azure Machine Learning, Databricks, and Cloud-based AI Deployments.
• Strong knowledge of MLOps/LLMOps, model versioning, monitoring, and CI/CD pipelines.
• Experience developing and integrating REST APIs, WebSockets, and Event-Driven Architectures.
• Familiarity with Git, Jenkins, Jira, Confluence, SDLC, and Agile methodologies.
• Experience using AI-assisted development tools such as GitHub Copilot, Windsurf, or Codeium.
• Good understanding of enterprise security, governance, compliance, and AI best practices.
• Excellent communication, stakeholder management, analytical thinking, and problem-solving skills.