- Lead the architecture and implementation of GenAI services with robust prompt/tool use, function calling, and workflow orchestration; enforce caching, retries, and token/cost controls.

- Design and optimize RAG pipelines (indexing, chunking, embeddings, rerankers) and evaluate retrieval/answer quality; advance to complex agentic patterns (multi-tool, multi-step, multi-agent).

- Apply advanced NLP/Transformer techniques (fine-tuning, adapters/LoRA, distillation) aligned with business and data constraints.

- Engineer production-grade Python services/APIs; integrate vector stores (FAISS, Pinecone), LangChain/LlamaIndex, streaming, and guardrails.

- Ensure operational excellence on AWS/Azure with observability, security, and governance frameworks.

- Mentor junior engineers, establish coding standards, and lead technical reviews to maintain high-quality deliverables.

Must Have Skills :

- Deep expertise in GenAI foundations (LLMs, embeddings, prompting).

- Proficiency with Transformer architectures (Hugging Face ecosystem, fine-tuning strategies).

- Advanced NLP applied skills (text processing, evaluation metrics).

- Hands-on experience with RAG and agentic AI design and implementation.

- Strong Python development skills and cloud experience (AWS/Azure).

- API development for model-backed experiences and enterprise integration.