The problems here are genuinely novel. How do you present AI-extracted insights alongside source documents so a professional trusts them enough to make a $100M investment decision? How do you reason about agentic systems, evaluations, and probabilistic output, and still ship something customers rely on every day? How do you take something bespoke and turn it into something repeatable that ships?

Imagine it's Month 1. You've diagnosed, delivered, and productified a major customer deliverable — taken something bespoke and made it repeatable. You're in customer sessions forming strong opinions on where the product is failing them, and pushing engineering on it. You know where the product wins demos and where it loses them. That's the pace.

What You'll Do

• Own and ship a product area. You own the product layer for your area end-to-end, customer insight through to pixel-level delivery, working shoulder-to-shoulder with engineering. We ship daily; you will too.
• Turn vision and feedback into product. Take product direction and live customer feedback and convert it into sharp, shipped product, cutting scope, making the call, and holding the bar.
• Get close to customers. Spend real time with enterprise customers, including the high-stakes conversations (renewals, a broken workflow, a promise made and kept). Bring what you learn straight back into the product.
• Drive adoption and revenue. Sharpen how the product demos and sells so it visibly drives adoption and revenue, not just feature count. You'll see your decisions in the numbers.
• Invent AI-native product. Agentic workflows, streaming outputs, document intelligence, confidence signals, human-AI collaboration. There's no playbook, you'll help write it, and use AI tools to collapse the gap between idea and shipped.
• Keep the signal flowing. Bring light, reliable process, the consistent weekly updates and shared context that keep founders, engineering, and customers aligned without slowing anyone down.

About You

You're a senior product person who never stopped building. You've shipped product to real customers and you shipped something yourself in the last 12 months, you can open Figma, write a brief, prototype in AI tools, cut scope, and make the call. You're commercially wired: you think about adoption and revenue, not just what made it into the release.

You're genuinely AI-native. You've shipped AI product that customers use, you have opinions about agentic systems, and you can reason about evaluations and probabilistic output. That shows up in your own craft too, you work in AI-native tooling, you'll ship a small code change to unblock yourself, and AI has genuinely changed how you work. "I use ChatGPT and Figma sometimes" isn't what we mean.

You've been in the high-stakes customer conversations, a renewal on the line, a product that broke, a promise you had to make and keep, and you can talk through exactly how you handled them. You thrive in startup pace: high ownership, comfortable with ambiguity, curious, and an active communicator. You bring just enough process to be consistent, because you know that's where founders often need the most help.

What We're Looking For

• Shipped AI product that real customers use, with real opinions on agentic systems, evaluations, and probabilistic output. (Must-have.)
• Deep personal AI craft, AI-native in your own workflow (e.g. AI-native tooling, shipping small code changes yourself), not AI as a novelty. (Must-have.)
• A commercial mindset, you measure yourself on adoption and revenue, and you understand how enterprise buyers evaluate, adopt, and expand. (Must-have.)
• Still a builder, shipped product personally in the last 12 months: opens Figma, writes briefs, prototypes, cuts scope, makes the call.
• Battle-tested in high-stakes customer conversations, renewals, a broken product, promises made and kept, and able to walk through them in detail.
• Thrives in startup pace, high ownership, comfortable with ambiguity, curious, an active communicator, and brings just enough process to stay consistent.

Nice to Have

• Domain knowledge in a specialist professional field, real estate, finance, legal, insurance, healthcare, or construction. Not required, but we expect you to do the research.
• Experience with complex data products, extraction, search, intelligence, analytics, not pure SaaS CRUD.
• Platform instinct, thinks in systems, APIs, skills, and compounding, not just features.
• Can touch code, enough to prototype or unblock yourself.

Your First Few Months

• Month 1. You've diagnosed, delivered, and productified a major customer deliverable, turned something bespoke into something repeatable that ships. You're in customer sessions forming strong opinions on where the product is failing them and pushing engineering on it. You understand the product: where it wins demos and where it loses them.
• Month 3. Deep customer wins from the product being closer to customers than it's ever been, at least one account where the breakthrough came from you. The first measurable improvements to how we demo and sell are live, and you're on top of the metrics that matter: latency, trust, accuracy, adoption.
• Month 6. The product is the reason we're winning deals we wouldn't have won six months ago. Multiple deep customer wins where the compound effect is visible, better data, better workflows, higher adoption, expansion revenue, and product-led growth that's real and measurable, not a narrative.

Compensation and Benefits

• We're hybrid three days a week in our New York (preferred) or London office.
• New York: $185,000–$220,000 base, plus meaningful equity. Flexible based on experience and seniority
• London: £100,000–£135,000 base, plus meaningful equity. Flexible based on experience and seniority
• Meaningful equity on a standard vesting schedule 📈
• 401