AI/RAG engineer

Responsibilities

• Building AI search agents- including ReAct, planning, and multi-agent architectures via custom implementation or frameworks like LangGraph, Dify, or CrewAI.
• Building end-to-end RAG pipelines from ingestion, chunking, embeddings, and hybrid vector search, ideally using Opensearch.
• Operating and monitoring vector/hybrid indexes (e.g. OpenSearch) in production environments.
• Implement grounding and citation to link generated answers back to their exact source passages.
• Automate evaluation using synthetic QA, retrieval-hit-rate tracking, and model-critique loops to continuously measure accuracy and detect drift.
• Orchestrating external tools or knowledge bases and monitoring latency and cost at production scale.

Languages