Python, AI/ML, GenAI, RAG & Agentic AI_Virtual Interview_23 Oct

Tata Consultancy Services Limited; Chennai, Bengaluru; On-site; INR 2,000,000 - 4,000,000; Full time

Job summary

Tata Consultancy Services Limited is seeking experienced AI/ML professionals in India to design, build and deploy GenAI solutions. You will work on Python-based AI pipelines, RAG architectures, and agentic AI workflows, integrating LLMs with enterprise systems and tools.

Candidates should have hands-on experience with modern frameworks and cloud AI services. The role focuses on scalable, secure AI development, collaboration with engineering and business teams, and delivering practical GenAI

Qualifications

• Hands-on Python development experience.
• Solid AI/ML concepts and model implementation know-how.
• Experience with Generative AI and LLMs.
• Develop RAG-based applications.
• Knowledge of embeddings, vector databases, semantic search, prompts.
• Familiarity with LangChain, LlamaIndex or similar frameworks.
• Experience with Agentic AI and AI agents, including tool integration.
• Knowledge of REST APIs, JSON, Git and deployment practices.

Responsibilities

• Design and develop Python AI/ML and GenAI applications.
• Build and optimize RAG pipelines for enterprise use cases.
• Create Agentic AI workflows with tool integration and multi-step tasks.
• Integrate LLMs with apps, APIs, databases and knowledge sources.
• Tune prompts and retrieval strategies for GenAI performance.
• Collaborate with teams to translate requirements into scalable AI solutions.
• Follow security, privacy, testing and responsible-AI practices.

Skills

Python

AI/ML concepts

Generative AI

LLMs

RAG pipelines

Embeddings

Prompt engineering

LangChain

LlamaIndex

Agentic AI

Tool integration

REST APIs

Tools

LangChain

LlamaIndex

LangGraph

AutoGen

Semantic Kernel

Docker

Kubernetes

CI/CD

Pinecone

FAISS

Job description

Job Description Python, AI/ML, GenAI, RAG & Agentic AI

Experience: 5-10 Years
Locations: Delhi, Chennai, Bangalore, Kochi, Hyderabad

Interview Mode: Virtual
Interview Date: 23rd October 2026

Job Summary

We are looking for experienced professionals with strong expertise in Python, Artificial Intelligence/Machine Learning (AI/ML), Generative AI, Retrieval-Augmented Generation (RAG), and Agentic AI. The ideal candidate should have hands-on experience building and implementing AI/GenAI solutions using modern frameworks and Large Language Models (LLMs).

Must-Have Skills

• Strong hands-on experience in Python development
• Good experience in AI/ML concepts, model development, and implementation
• Hands-on experience with Generative AI and Large Language Models (LLMs)
• Experience developing RAG-based applications
• Knowledge of embeddings, vector databases, semantic search, and prompt engineering
• Experience working with LLM frameworks such as LangChain, LlamaIndex, or similar frameworks
• Hands-on exposure to Agentic AI / AI Agents, including tool integration and multi-step workflows
• Experience integrating LLM APIs and AI services
• Understanding of REST APIs, JSON, Git, and deployment practices
• Ability to design, develop, test, and troubleshoot scalable AI solutions

Good-to-Have Skills

• Experience with Azure OpenAI, AWS Bedrock, Google Vertex AI, or similar cloud AI platforms
• Knowledge of vector databases such as Pinecone, FAISS, Chroma, Weaviate, or Azure AI Search
• Exposure to MLOps / LLMOps, model monitoring, evaluation, and deployment
• Knowledge of frameworks/tools such as LangGraph, AutoGen, or Semantic Kernel
• Experience with Docker, Kubernetes, or CI/CD pipelines

Key Responsibilities

• Design and develop AI/ML and Generative AI applications using Python.
• Build and enhance RAG pipelines for enterprise use cases.
• Develop Agentic AI workflows capable of tool usage and multi-step task execution.
• Integrate LLMs with enterprise applications, APIs, databases, and knowledge sources.
• Optimize prompts, retrieval strategies, and overall GenAI application performance.
• Collaborate with engineering and business teams to translate requirements into scalable AI solutions.
• Follow appropriate security, privacy, testing, and responsible-AI practices.

Note: Candidates with an official 90-day notice period are preferred.