Senior Staff Applied AI Engineer - Context Retrieval
Core
Building the foundational retrieval stack and search subagents that enable Databricks agents to retrieve, reason about, and ground context from enterprise SaaS data.
Role type
Senior Staff Applied AI Engineer (Information Retrieval & Agentic Systems)
Builds
End-to-end retrieval systems (query/content understanding, indexing, ranking) and agentic search layers for Databricks agents.
Domain
Enterprise Data & AI Infrastructure / Information Retrieval / Agentic AI
Deliverable
production ML models | infrastructure
Required skills
Information Retrieval (IR), RAG architectures, hybrid retrieval, learning-to-rank, agentic system design, relevance evaluation, structured/unstructured data indexing, 0→1 system building, technical leadership
Preferred skills
Enterprise SaaS retrieval, agentic systems, open-source IR contributions, model fine-tuning
Technologies
BM25, Lucene, Elasticsearch, OpenSearch, FAISS, ScaNN, HNSW, cross-encoders, LLM-as-judge
Responsibilities
Design and build the full retrieval stack from scratch; Connect to heterogeneous SaaS data sources; Optimize retrieval for both LLMs and human users; Develop query understanding and content understanding pipelines; Build search subagents for multi-hop reasoning and sufficiency checks; Establish evaluation frameworks for retrieval and agent decisions; Set technical direction and mentor senior engineers
Seniority
Senior Staff, hands-on IC with strategic leadership
