- Expertise in Machine Learning, Deep Learning, NLP, Transformers, model optimization and evaluation, with extensive hands-on experience using Python, PyTorch/TensorFlow, and up-to-date AI frameworks.
- Proven experience designing and developing enterprise-grade LLM/Generative AI solutions, including model selection, prompt/context engineering, fine-tuning, tool calling, and inference optimization.
- Experience in architecting production-grade RAG solutions, including advanced chunking, embeddings, hybrid retrieval, vector databases, reranking, query transformation, grounding, citations, and retrieval optimization.
- Hands-on expertise in Agentic AI architectures using LangGraph, LangChain, or equivalent, including orchestration, state/memory, tool calling, conditional workflows, retries,



and human-in-the-loop patterns.
- Experience with MLOps/LLMOps, Docker, Kubernetes, CI/CD, model monitoring, observability, evaluation, and production troubleshooting across cloud and/or on-premises deployments.
- Experience in optimizing AI solutions for accuracy, latency, scalability, GPU utilization, concurrency, token consumption, and infrastructure/API costs.
- Strong understanding of Responsible AI, security, privacy, guardrails, prompt-injection protection, hallucination mitigation, and enterprise AI governance.
- Experience in working on government projects is a plus.

📌 Generative AI Engineer (New Delhi)
🏢 KPMG India
📍 New Delhi