Senior Staff Applied AI Engineer - Context Retrieval

<p>P-1549</p> <p>At Databricks, we are passionate about enabling data teams to solve the world&39;s toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world&39;s best data and AI infrastructure platform so our customers can use deep data insights to improve their business.</p> <p><strong>The Mission</strong></p> <p>Databricks agents are only as good as the context they can retrieve. Whether an agent is answering a question about last quarter&39;s revenue, debugging a failing job, generating SQL against a 10,000-table lakehouse, or summarizing a Wiki page, its quality is bounded by what it can find — and how well it understands what it finds.</p> <p>We are hiring a <strong>Senior Staff Applied AI Engineer</strong> to own <strong>context retrieval for Databricks agents across SaaS providers</strong>. This is a zero-to-one role with two deeply connected charters:</p> <ol> <li><strong>Build the retrieval stack</strong> — query understanding, content understanding, ranking, retrieval, and evaluation — across the Enterprise SaaS data stored across multiple systems.</li> <li><strong>Build the search subagents</strong> that sit on top of that stack and reason about <em>what context is needed</em>, <em>how to retrieve it</em>, and <em>whether the right thing actually came back</em> — closing the loop between an agent&39;s intent and the substrate that serves it.</li> </ol> <p>If you have deep Information Retrieval wisdom, have shipped retrieval systems for RAG and agentic workloads, and want to build the substrate — and the agents on top of it — that make every Databricks agent measurably smarter, this role is for you.</p> <p><strong&g