We’re building AI agents for GTM — agents that do the work of a revenue team end-to-end: researching accounts, drafting outreach, updating the CRM, triaging inbound, prepping calls, following up. GTM data is the messiest data in the enterprise. It lives across 10+ systems, it’s stale, it’s permissioned, and full of half-truths people typed into Salesforce on a Friday afternoon. Building agents on top of this without hallucinating and actually get the job done at scale is the real engineering problem.
You’d be the first engineer. The hard part isn’t the agent loop — it’s the data and context layer underneath : pulling from Salesforce, HubSpot, Gong, Slack, Notion, Drive and a long tail of broken APIs, then turning that mess into the precise, fresh, permission-aware context an agent needs to take a real action. Most of your hardest engineering time will be on the data side: ingestion, modelling, freshness, retrieval quality, evals, latency, permissions.
Own the data and context pipeline end-to-end: connectors, ingestion, schema modelling, chunking, embedding, indexing, hybrid search, reranking, serving. Own the agent runtime on top: tool use, planning, multi-step execution, error recovery. Build the eval harness before shipping anything new. We don’t ship on vibes. By month six you’ll have hired the second engineer and shaped the team’s culture around data quality, evals, latency, and product taste.
5+ years of production backend experience, with meaningful time on data-heavy systems — retrieval, search, recsys, streaming pipelines, or ML infra with real users and real SLAs.~ You think data first . Bad data in, bad agents out, and you’ve felt that pain.~ Shipped a non-trivial RAG, semantic search, or agent system end to end. Strong opinions on hybrid retrieval. You know when BM25 beats embeddings, when SQL beats both, and you’ve made those calls in production.~ nice to have) Python or Go fluency.
Multi-tenant systems with row- or document-level access control. Messy GTM stack integrations — Salesforce, HubSpot, Gong, Outreach, Apollo — and the scars to show for it. Data governance or security overlap: lineage, audit trails, PII handling, prompt injection defence,
Founders call (60 min, remote). Walk us through a data-heavy system you’ve built.# 25 days holiday + UK bank holidays….