We're looking for a AI Product Builder to help define the next chapter of the browser – someone who ships their own prototypes, holds strong opinions on craft, and doesn't wait to be told where to start. You'll own a product area end-to-end: frame the opportunity, build the prototype that sells it, ship the experience alongside design and engineering, and measure how it lands.
What You'll Do
Own product areas end-to-end, from discovery through post-launch iteration.
Turn ambiguous opportunities into opinionated proposals, backed by research, data and working prototypes.
Prototype the experience yourself – in Cursor, Claude, Figma, or whatever gets an idea into something people can feel.
Partner with and ship alongside design and engineering, from kickoff to polish.
Monitor performance post-launch and make the call on what comes next.
Requirements:
4+ years shipping consumer or large-scale complex digital products – as a PM, designer, engineer, or in a hybrid role.
A track record of shipping thoughtful, user-centered features end-to-end and iterating on real data.
Strong product sense: simplifying complexity, seeing around corners, getting into details.
Design taste and UX judgment – specific, defensible opinions about flows, motion, and microcopy.
Technical fluency: comfortable reading a spec, pushing on architecture, and working with engineers as peers.
AI-native in practice: you build with AI – prototypes, experiments, automations, agents, not just documents.
Analytics baseline: comfortable thinking in SQL-shaped questions and finding the real signal.
Clear, concise communication – written and verbal.
4+ years shipping consumer or large-scale complex digital products – as a PM, designer, engineer, or in a hybrid role.
A track record of shipping thoughtful, user-centered features end-to-end and iterating on real data.
Strong product sense: simplifying complexity, seeing around corners, getting into details.
Design taste and UX judgment – specific, defensible opinions about flows, motion, and microcopy.
Technical fluency: comfortable reading a spec, pushing on architecture, and working with engineers as peers.
AI-native in practice: you build with AI – prototypes, experiments, automations, agents, not just documents.
Analytics baseline: comfortable thinking in SQL-shaped questions and finding the real signal.
Clear, concise communication – written and verbal.
This position is open to all candidates.
