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Senior LLM Engineer RAG & AWS Bedrock
LLM Engineer
Lead the design and deployment of large‑language‑model applications using Retrieval Augmented Generation on AWS Bedrock, building scalable chatbot APIs with ChromaDB and API Gateway.
About the role
Key Responsibilities
- Architect and implement end‑to‑end LLM pipelines that combine Retrieval Augmented Generation with Amazon Bedrock models.
- Design, develop, and maintain high‑performance chatbot APIs using AWS API Gateway and Lambda.
- Integrate and optimize vector store solutions such as ChromaDB for fast semantic search.
- Write production‑grade Python code, create reusable libraries, and ensure robust testing and monitoring.
- Collaborate with data scientists and product teams to translate research prototypes into scalable cloud services.
Requirements
- 5+ years of software engineering experience, with a focus on LLM/AI systems.
- Deep expertise in AWS services, especially Bedrock, API Gateway, Lambda, and IAM.
- Strong knowledge of Retrieval Augmented Generation techniques and vector databases (e.g., ChromaDB).
- Proficiency in Python and modern AI frameworks (e.g., LangChain, PyTorch, TensorFlow).
- Experience building, deploying, and monitoring production APIs at scale.