A GenAI (Generative AI) Architect with 814 years of experience bridges deep software engineering leadership and enterprise AI strategy, designing production-grade, scalable LLM and multi-agent systems.

Core Responsibilities
- Enterprise Architecture Design: Translate business use cases into robust target architectures using cloud platforms like AWS Bedrock, Azure AI Foundry, or Google Vertex AI.
- Agentic AI & Orchestration: Build autonomous systems and multi-agent collaboration frameworks using tools like LangChain, LangGraph, and Model Context Protocol (MCP) servers.
- LLMOps & Governance: Implement CI/CD pipelines, evaluation metrics, security guardrails, and cost governance aligned with frameworks like the EU AI Act or NIST AI RMF.
- Technical Leadership: Guide engineering teams and advise CxOs on enterprise AI adoption, fine-tuning strategies (LoRA, RAG), and vector database integration.

Key Requirements & Skills
- Experience: 814 years in total IT/software engineering, with 3–5+ years specialized in AI/ML and Generative AI.
- Tech Stack: Advanced Python, PyTorch/TensorFlow, Hugging Face, vector databases (Pinecone, FAISS, PGVector), and LLM APIs (OpenAI, Claude, Gemini)

📌 Gen AI Architect (Mumbai)
🏢 Tata Consultancy Services
📍 Mumbai