Job 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
Qualifications Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field 3+ years of experience in developing AI systems, with a focus on retrieval-augmented generation (RAG) Proven track record in building and ...