About the job
We are hiring a Senior Staff Applied AI Engineer to own context retrieval for Databricks agents across SaaS providers. This is a zero-to-one role with two deeply connected charters: Build the retrieval stack and build the search subagents that sit on top of that stack and reason about what context is needed, how to retrieve it, and whether the right thing actually came back.
Responsibilities
Build the full retrieval stack from scratch; Retrieve across heterogeneous data — structured and unstructured; Connect to the SaaS surface area customers actually use; Optimize for two consumers at once; Crack query understanding for agents; Crack content understanding at scale; Build search subagents that reason about retrieval; Build the evaluation flywheel for both retrieval and subagents; Set technical direction and grow the team.
Qualifications
Minimum
10+ years of software engineering experience, with significant time spent building production retrieval, search, or RAG systems at scale; Deep Information Retrieval (IR) expertise; Hands-on experience with modern LLM-era retrieval; Experience designing agentic systems on top of retrieval; Strong grasp of relevance evaluation; Experience working across structured and unstructured data; Track record of building 0→1; Demonstrated ability to operate as a technical leader.
Preferred
Experience building retrieval over enterprise SaaS sources; Background in agentic systems, tool use, or multi-turn retrieval for LLM agents; Contributions to open-source IR/search projects, or publications at SIGIR, KDD, WWW, EMNLP, or similar venues; Experience training or fine-tuning embedding models, rerankers, or query understanding models.