Senior/Staff Software Engineer (Search & Retrieval)

<div class="content-intro"><h3 class="" data-start="443" data-end="463">About Actively AI</h3> <p><a href="http://www.actively.ai/">Actively AI</a> is defining a new category: Intelligence-Led Revenue.</p> <p>Revenue organizations have always been bottlenecked on human capacity. Reps triage which accounts get attention. Context disappears at every handoff. On any given day, the vast majority of accounts have exactly zero people thinking about them.</p> <p>Actively addresses this at the structural level. Our platform deploys Per-Account AgentsTM across our customers’ TAM, working 24/7 to research, identify opportunities, and advance next steps without being asked. Leading enterprises including Ramp, Ironclad, and Samsara are already making this shift.</p> <p>Our co-founders are former Stanford AI researchers, and the team comes from Harvard, CMU, Berkeley, Brex, Scale AI, and Google. We've raised $68M from TCV, First Harmonic, Bain Capital Ventures, First Round Capital, and more.</p></div><h3><strong>About the Role</strong></h3> <p>We’re looking for a <strong>Senior / Staff Software Engineer - Search &amp; Retrieval</strong>&nbsp;to build and scale the systems that power Actively’s AI agents to find, rank, and reason over data.</p> <p><strong>&nbsp;</strong></p> <p>When an Actively agent decides which account to prioritize or what action to take next, it reasons over retrieved context; data pulled from customer records, call transcripts, signals, and internal intelligence. Get that retrieval right and the agent acts with precision. Get it wrong and it doesn't matter how good the underlying model is.</p> <p><strong>&nbsp;</strong></p> <p>You'll design and build the search, retrieval, and relevance infrastructure that feeds every agent at Actively from the enrichment and entity extraction that turns raw data into something queryable, to the ranking systems that determine what context an agent actually sees. The data is diverse, messy, and customer-specific. Freshness matters. So does precision. And the consumer isn't a human browsing results but it's a model that will act on whatever you give it.&nbsp;</p> <h3><strong>What You’ll Do</strong></h3> <ul> <li><strong>Build the retrieval layer agents depend on.</strong> Design and scale the search and retrieval infrastructure that feeds Actively's agents, covering indexing, querying, ranking, and filtering across diverse customer data sources.</li> <li><strong>Turn raw, unstructured data into something retrievable.</strong> Design enrichment and entity extraction systems that pull structure, relationships, and context out of call transcripts