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We're hiring Full-Stack Product Engineer who will own customer-facing features end to end on a data-intensive platform: 100k+ rows, instant search, real-time updates, complex filtering — from the first product decision to what ships in front of users. You decide what to build, direct AI agents to build it, and verify the result. We don't hand out fully-specced tickets. What you'll do Own features from a rough idea to production — decide what to build, cut scope, ship something usable fast, then iterate from real usage Make the product calls yourself, with design and GTM, instead of waiting for a spec Direct AI agents as a core part of how you build: parallel exploration, precise briefs, delegated implementation, verified output Build and own data-heavy features at scale in React, Node.js and PostgreSQL — filtering, faceting, saved views, real-time updates — including the query, index and rendering work that keeps them fast Implement the interaction layer that makes heavy data feel light: optimistic updates, conflict resolution, retry queues Build the harness that lets you trust agent output without reading every line — tests, evals, automated review, context systems You may be a fit if You lead with the user and the problem, not the stack — and you decide rather than list options You've shipped something nobody specced for you, and can name a trade-off you made to ship faster You have a real, daily AI-orchestration workflow (Claude Code, Cursor, Copilot) and can describe how you direct agents — where you delegate, where you keep control, how you verify You're comfortable across React/TypeScript and Node.js/PostgreSQL without being narrowly specialised in one You understand database performance well enough to know what will strain at 10× — indexes, query shape, pagination — without needing to hand-write every query You reason about the business unprompted: who pays, what converts, what it costs Nice to have You've built tooling around agents — evals, automated review, context or skills systems. This is rare, and we weight it heavily. Elasticsearch or other search-engine experience Real-time collaboration stack (WebSockets, Liveblocks) Startups, or products built from scratch Open-source contributions or public side projects Feature flags, product analytics (PostHog/Amplitude), error monitoring Shipped AI features before Why this role is important We're not hiring for the ability to write code — AI writes it now, fast and well. We care more about what you've owned than about years on a CV. If you're fast, product-minded and orchestrate well, apply even if your experience is shorter than a typical senior listing. What's scarce is judgment: knowing what to build, deciding quickly, directing agents at the right altitude, and verifying their work. So this seat is weighted toward product ownership and AI orchestration, with real engineering depth where it still counts — at scale, and in what you guarantee. What we offer Remote within Europe A small, autonomous team — no micromanagement, no ticket queue Real ownership of a customer-facing surface, and the speed that comes with it Competitive comp + benefits Our interview process Recruiter pre-screen — a short call about how you work, what you've built, and how you actually use AI. (45 min) An intro with call with Team Lead about the product and the challenges.(30 min) A live, AI-driven technical round — a real production codebase, an intentionally under-specified feature, work an AI coding agent, and full autonomy over how you approach it. No spec, no acceptance criteria, on purpose. We're watching how you meet ambiguity, where your control sits, and whether you ship something real. (90 min) Originally posted on Himalayas