Tata Consultancy Services→

GenAI / Agentic AI Engineer (LLM, LangGraph, RAG) at Tata… · Hyderabad

ExperiencedOn-siteHyderabad

Skills

GenAILangGraphRAGLLMPythonFastAPIArtificial Intelligence

Key Responsibilities

Design, develop, and deploy AI-powered applications using LLMs, Agentic AI frameworks, and modern AI architectures.
Build and orchestrate multi-agent systems using LangGraph, A2A, MCP, and related frameworks.
Design and implement scalable RAG pipelines using vector databases, embeddings, and semantic search.
Develop REST APIs and AI services using Python, FastAPI, and Pydantic.
Integrate AI solutions with AWS, Azure, or GCP cloud services.
Build and optimize prompt engineering, tool-calling, and agent workflows.
Develop LLM evaluation, monitoring, and optimization frameworks.
Create AI-driven user experiences and business workflows powered by intelligent agents.
Collaborate with business, compliance, IT, and data teams to deliver enterprise AI solutions.
Leverage AI-assisted development practices for code generation, testing, documentation, and refactoring.
Implement cloud-native deployment strategies using Docker, CI/CD, and modern DevOps practices.
Stay updated on emerging GenAI, Agentic AI, and LLM technologies.

Required Skills

8+ years of Software Engineering or Data Science experience.
Minimum 2+ years of hands-on experience in Generative AI, LLMs, or Agentic AI solutions.
Strong expertise in Python development.
Experience building AI Agents using LangGraph and related agent frameworks.
Strong knowledge of LLMs, embeddings, prompt engineering, and tool integrations.
Hands-on experience with Retrieval-Augmented Generation (RAG) architectures.
Experience developing APIs using FastAPI and Pydantic.
Experience with MCP (Model Context Protocol) and A2A integrations.
Knowledge of cloud platforms such as AWS, Azure, or GCP.
Experience with Docker, CI/CD pipelines, and cloud-native architectures.

Preferred Skills