About the Role
We are seeking an experienced LLM Engineer to join a collaborative team working on backend features for a Retrieval-Augmented Generation service.
Your primary focus will be developing and optimizing RAG models for search across large-scale medical and scientific documents, including pre-processing and embedding over half a billion documents to ensure they are searchable and contextually accurate.
* Semantic chunking strategies
* Improving the automated evaluation pipeline
* Fine-tuning LLMs for textual RAG use cases
The role involves hands-on experimentation, model development, and backend engineering, with deployments to non-prod environments and collaboration with DevOps for production rollout.
Key Requirements:
* 1+ years of experience as a Search Engineer or AI Engineer
* Search Technology Experience – OpenSearch, building scalable search systems
* 2+ years of Python development experience, including API creation, model training, testing, and general backend programming
* Familiarity with LangChain for building LLM workflows using tools, memory, and retrieval.