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Generative and Agentic AI Engineer

Role summary

You will design and ship GenAI capabilities and agentic AI workflows—grounded in NLP/Transformers—including RAG systems and advanced multi agent patterns. You’ll build protected, observable, and cost aware LLM solutions on AWS/Azure, integrating with product backends and enterprise data.

Key responsibilities
- Build GenAI services with robust prompt/tool use, function calling, and workflow orchestration; implement caching, retries, and token/cost controls.
- Implement RAG pipelines (indexing, chunking, embeddings, rerankers) and evaluate retrieval/answer quality; progress to advanced agentic patterns (multi tool, multi step, multi agent).




- Apply NLP/Transformer techniques (fine tuning, adapters/LoRA, distillation) when justified by business and data constraints.
- Engineer production Python services/APIs; integrate vector stores (FAISS, Pinecone), LangChain/LlamaIndex, streaming, and guardrails.
- Operate solutions on AWS/Azure with proper observability, security, and governance hooks.

Must have skills
- GenAI foundations (LLMs, embeddings, prompting)
- Transformers (Hugging Face ecosystem, fine tuning strategies)
- NLP applied skills (text processing, evaluation metrics)
- RAG / advanced agentic AI design and implementation
- Python, AWS/Azure
- API development for model backed experiences

Qualifications and experience
- B.Tech/M.Tech/MS in CS/EE or equivalent.
- 4+ years in GenAI/NLP/AI Engineering

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