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Niche RAG/retrieval skills reduce pool, but metro location and established global employer increase competition.
Specialized retrieval engineering skills are moderately transferable across industries but require specific RAG and governance experience.
Explicit 7+ years and mandatory production retrieval, security, and pipeline experience create high shortlisting strictness.
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Design, build, and operate enterprise-grade data ingestion and retrieval systems for AI agents and knowledge-search platforms.
Improve retrieval quality metrics such as Recall@K, Precision@K, citation accuracy, and reduce latency and operational cost.
Own governance and security measures including access control, PII management, data lineage, and monitoring for retrieval systems.
7+ years experience in data engineering, backend, search engineering, machine learning engineering, or knowledge-platform development.
Strong hands-on experience with Python and SQL.
Production experience with Retrieval-Augmented Generation or enterprise search solutions involving vector databases and embedding models.
Knowledge of data security, privacy, role-based access controls, and production observability.
Experienced in building scalable data pipelines for structured and unstructured data across enterprise knowledge bases and multi-source ingestion.
Proficient in advanced retrieval techniques including vector/hybrid retrieval, reranking, semantic search, and citation-grounded responses.
Capable of partnering with cross-functional stakeholders (AI, platform, security, business) and managing operational readiness including monitoring, alerts, and runbooks.