greatquestion - Product Engineer (AI / Full-Stack)

• How you work. AI is embedded across your entire workflow - not just used for coding. You might spend a morning digging through interview transcripts and product analytics to understand a problem, build a few throwaway prototypes to see which approach holds up, and then build a technical plan before handing it to a couple of agents to build and QA. • We’re expecting great judgment around all of that: breaking work into sensible pieces, evaluating the output carefully, and most importantly, owning whatever ships, regardless of who typed it. • What you build. You build highly usable, customer-centric products that people love. You take the extra time to really dig into the data to make sure you understand the problem; and validate that what you’ve built actually solves it. You’ll go the extra mile to deliver something with UI + UX polish, while also thinking in systems to make sure that you’re using the right primitives so you’re delivering less bespoke solutions. • Who you are. We're a small team of exceptional engineers, and we only hire people who raise the bar. • Strong across the full stack. An expert in both exposing APIs and the frontend it sits upon. We’re a Rails and TypeScript team, but it’s not a hard requirement. • Built and run production systems. Shipping features live and then maintaining them long enough to see what works (and what doesn’t!) • Live in an agentic coding harness daily (Claude Code, Codex, Cursor - we don't care which) and have real opinions about your setup. • Ideally shipped LLM-powered features, or least know what it takes to run them in production. • Have shipped things where you decided what to build, and can defend your UX opinions. • Write clearly. We're remote and async-heavy; people who write clearly think (and prompt) clearly. • Are senior (roughly 5+ years with real ownership). Our level grading is tougher than most. • We've rebuilt how we work around AI agents, to ensure our engineers are unblocked to work at AI native speeds: • Main goes to production and approvals aren’t always required. Fast, automated CI is the gate, and we trust people to make the right judgements. Good work goes live as soon as it’s finished. • We invest in making the codebase easy to work in: written runbooks and conventions that help agents and new people find their way around quickly. • Running a few agents in parallel is easy, and expected. Sandboxes and preview environments are trivial to spawn. • You'll always have the latest tools and models, and we're generous with tokens. • Light on ceremony, high on accountability and communication. • This might not be for everyone, but if it excites you, please apply. We’re especially keen to meet people who are willing to challenge some of these ideas with their own hard-won lessons from the arena. • YOUR FIRST 90 DAYS • We expect you to hit the ground running, and fast. • Week 1: use the harness to learn the codebase and merge your first PR, ideally on day one. You’re deep in the customer data, in their Slack channels, and solving problems. • First 30 days: ship into a live area. That might be AI Moderator quality, or working directly on our global chat experience. You understand the product, the competitors, the problems we’re solving, and have a view on how we can win. • By 60 days: You own a surface - how the research agent communicates findings, growing our MCP surface, or rebuilding a core page on the new design system. • By 90 days: you're deep on a product area: talking to its customers, deciding what's next, accountable for whether it worked. You’re pushing the strategy with the founders & Head of Product in new directions with confidence. • WHO SHOULDN'T APPLY • Ambiguity and shifting priorities wear you down. Problems arrive here half-shaped, and the roadmap has changed under our feet more than once this year. Some people find that energizing; if you don't, you'll hate it. • You wait to be unblocked. We’re a small team, remote, and with light processes… resourcefulness is critical to the job. We need people who unblock themselves. • You’re not all-in on AI. Dabbling won't cut it here. Agents are how we work, not a thing we're trying out. • You'd rather not talk to customers. Product engineers here get on calls, read transcripts, and sit in the support queue sometimes. That closeness is the whole point of the role. • You only want the shiny work. Plenty of weeks are polish, reliability, and making something 5% less annoying. • You want a PM to frame the problem and hand you a spec. “Just tell me what to build and I’ll build it” will not fly here.