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Experience: 7+ Years Location: Pune / Gurgaon (Hybrid) Job Summary We are looking for an Agentic AI Developer with hands-on experience in building production-grade LLM applications, AI Agents, and RAG solutions. The ideal candidate should have solid Python development skills and experience with contemporary Agentic AI frameworks to design, develop, and deploy scalable AI solutions. Key Responsibilities Build LLM-based applications and multi-agent workflows using LangChain, LangGraph, CrewAI, AutoGen, Microsoft Agent Framework, or LlamaIndex. Develop RAG pipelines including chunking, embeddings, vector search, and re-ranking. Build AI agents with tool calling, memory management, and Human-in-the-Loop (HITL) capabilities. Design effective prompts, structured outputs, and fine-tune LLMs using LoRA/PEFT. Develop REST APIs using FastAPI and integrate enterprise applications. Work with Pinecone, Qdrant, or pgvector for vector search. Deploy AI applications using Docker, Kubernetes, AWS/Azure, and maintain CI/CD pipelines. Implement AI observability, guardrails, hallucination detection, and performance optimization. Collaborate with architects and cross-functional teams to deliver enterprise AI solutions. Mandatory Skills Agentic AI & Generative AI Python, FastAPI LangChain, LangGraph (CrewAI/AutoGen/LlamaIndex is a plus) RAG, LLMs, Prompt Engineering Vector Databases (Pinecone/Qdrant/pgvector) Docker, Kubernetes AWS or Azure REST APIs, SQL, Git, CI/CD Valuable to Have LangSmith, RAGAS, TruLens, G-Eval MLflow, DVC LoRA, PEFT, Quantization Pydantic, vLLM, Triton Inference Server AWS/Azure AI Certifications Qualification B.E./B.Tech./M.Tech./M.Sc. in Computer Science, IT, AI, or related field. .
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In your interview, expect this: 'Walk me through the last time you had to debug something that took you more than an hour. What was it, what did you try first, and what would you do differently?' Hiring managers ask this to see if you think systematically or just try random fixes. Have a real example ready with specifics.