Key Responsibilities
- Application Development: Build and deploy applications using foundation models (e.g., GPT, Claude, Gemini, Llama) and APIs.
- RAG Implementation: Build Retrieval-Augmented Generation (a technique that lets AI search external data before answering) to ground outputs in factual company data.
- Agentic AI: Develop autonomous AI agents capable of multi-step reasoning and tool execution via APIs.
- Optimization & Fine-Tuning: Optimize model performance, reduce hallucinations (incorrect or made-up AI responses), and fine-tune open-source or closed-source models.
- Vector Databases: Implement vector stores (e.g., Faiss, Pinecone, Chroma) for quick semantic similarity search.
- Production & Monitoring: Deploy models securely, monitor latency and costs, and enforce responsible AI and data privacy guardrails.

Required Skills & Qualifications
- Programming: Advanced proficiency in Python (async programming, REST APIs).
- AI Frameworks: Hands-on experience with LangChain, LlamaIndex, or Hugging Face Transformers.

📌 GEN AI Engineer (Mumbai)
🏢 Tata Consultancy Services
📍 Mumbai