Tata Consultancy Services
Python, AI/ML, GenAI, RAG & Agentic AI_Virtual Interview_16th october
Skills
8 days ago
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Important information
Contract type:
Permanent
Location:
Bengaluru, Karnataka, India
Work mode:
Onsite
Published on:
15 October 2026
What they need
Job Description Python, AI/ML, GenAI, RAG & Agentic AI
Experience: 510 Years
Locations: Delhi, Chennai, Bangalore, Kochi, Hyderabad
Interview Mode: Virtual
Interview Date: 16th 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. Please apply if you meet this requirement.
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