Founding AI Engineer

Job Description Roles & Responsibilities We are hiring our Founding AI Engineer to own the agent layer of an AI-first fundraising platform: the conversational agents that run our warm outreach and investor relationships, and the matching engine behind them. Paires is where founders come to raise capital. We pair them with the right investors from a large, engaged global investor network, then our agents run the warm outreach and manage the relationships that turn into meetings. It is a two-sided platform, a product for founders and a living network on the investor side, not one-way matching. We are live with paying clients, profitable and self-funded, and we run as a small, senior, flat team that ships fast. The role You own our core: the agent system that runs the product - agents that research investors, draft outreach that reads human, and carry investor conversations end to end - plus the matching engine that pairs founders with investors behind them. You build it, you scale it, and you run it. This is the most important surface in the product, and it is yours. What you will own The agent layer: one orchestrator routing work to specialist agents. Those agents research investors, draft outreach that reads human, and carry investor conversations end to end. Evals gate what they are allowed to do alone. This is where you start. The matching engine behind it: embeddings, ranking, scoring, and the feedback loop that makes matches sharper over time. The backend and data behind it all: Python, Postgres, Supabase, AWS, clean pipelines. The agent layer is built on the Claude Agent SDK and Pydantic AI. Shipping to production end to end, and the judgment to know what to build next as we scale. You are a fit if you Have been one of the first engineers at a quick-growing company, running the show: you know what it takes to scale and deliver a product, not just manage it. Have at least 3 years of shipping production software behind you, and have taken a full app from zero to production and kept it running, end to end. This seat needs a whole-product builder, not only a model specialist. Have shipped LLM systems to production and have real examples you can walk us through, including an agent system that is more than a single prompt in a loop. Have built retrieval, ranking, or matching with embeddings in production. Write strong Python and reason clearly about data and systems. Design evals, because you care whether the output is actually good. Own outcomes end to end and move fast with AI tooling. You write the code yourself: this is a builder seat, not a management seat. There is no team to hand work to. Bonus: TypeScript in production, FastAPI, vector databases, fintech or fundraising. Company Industry BankingFinancial ServicesBroking Department / Functional Area IT Software Keywords Founding AI Engineer Get real-time job updates only on our App