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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 secure, 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
in CS/EE or equivalent.
4+ years in GenAI/NLP/AI Engineering

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