Founding Full-Stack Engineer

Build the system that matches people to jobs in a specialist market, runs the recruiters' day, and gives clients a live window into their searches. Then take the same template into the next sector. F&L Search places investment strategists, analysts and sales people with hedge funds, banks and research houses. Over the past year it has built an intelligence database of 35,000 people and a team of AI agents that source, screen, write and file under written instructions and review. The agents already do most of what a research team used to do. The product built on top of that needs an engineer who owns it. What you would build Matching. The core of the product: scoring candidates against live jobs on quality and fit, from CVs, calls, research and track record, so the best people surface first and the reasons are shown, not asserted.Enrichment. Company pages that grow themselves: every firm in the market with its people, moves, mandates and what has been learned about it, pulled from documents, calls and public sources and kept current.A workflow that leads the people. Today a recruiter decides what to do next; here the system does. It should put the right next action in front of a recruiter or an agent, with the evidence attached, and record what happened. The people respond to the workflow, not the other way round.Client portals that are actually used. Each client sees their searches, the people in them, where each person stands and what is coming, live. Functional, not a brochure. The boundary between the internal database and what a client can see is the product's promise, designed once and enforced by tests.Production. The database, backups, monitoring and uptime that paying clients depend on, and the security conversations with banks and funds before they sign. Why now, and why this is only the start This works in investment research recruitment because that market is deep, specialist and poorly served by generic tools. The architecture is not specific to it. A database of people and firms, agents that enrich it, matching, a workflow, and a client window apply to any specialist market where who-knows-whom decides outcomes. The plan is to prove it here, then repeat it sector by sector. The founding engineer builds the first one and owns the template. You would be the first technical hire, working directly with the founder and the firm's technical adviser, with meaningful equity and the authority that goes with it. Who this suits Five or more years building and running B2B software in production, ideally as an early engineer somewhere that grew.Strong in at least two of TypeScript and Next.js, Python, and Postgres, and willing on the third. Built on Supabase today.Has shipped matching, ranking, search or data-enrichment features, or wants to make them the centre of their work.Comfortable building with AI coding agents as the method, and sharp about reading their output critically.Serious about data boundaries and tenancy. Experience with financial clients or sensitive personal data is a strong plus.Able to work in London regularly. Right to work in the UK is required. This will suit someone who wants to own a product and a real stake in where it goes. It is less likely to suit someone who wants a large team around them, a narrow specialism, or a pure front-end role.