Duvo Inc - Product Engineer

• These are non-negotiables. The things we'll specifically evaluate you on: • Shipping and ownership. You've repeatedly taken ambiguous requirements to production. You own the full stack of a feature (UI, API, data, deployment) and you don't wait for someone to tell you what to build next. • Shipping and ownership. • Product judgment. You can define MVP scope, pick the right metric to move, and kill work that isn't delivering value. You think about what the user needs, not just what's technically interesting. • Product judgment. • AI comfort. You've worked alongside AI systems—at work or in side projects. You're comfortable building features that interact with LLM outputs (parsing agent responses, designing human-in-the-loop flows), but you won't be training models. • AI comfort. • Strong sense of product quality. You care about the details of how a feature looks and feels, not just whether it works. You notice when something is off and you fix it. • Strong sense of product quality. • Collaboration. You're low-ego and team-first. You give and receive direct and constructive feedback, align proactively with product and design, and unblock yourself and others. • Collaboration. • Judgment in a fast-moving environment. You'll often define your own scope based on customer problems surfaced through product feedback and competitive gaps — then ship it within a week. • Judgment in a fast-moving environment. • You might also • Have a strong sense for security and reliability in production systems. • Have scalable, distributed-system instincts—you've designed and operated systems that scale. • Have deep applied LLM experience—evaluation design, prompt engineering, safety controls, and cost optimization in production. • Have experience designing interfaces for AI-assisted workflows — confidence signals, human-in-the-loop interactions. • This is not for you if • You need significant hand-holding or aren't energized by figuring things out yourself. • You primarily want to work on infrastructure (see our SRE and AI Platform Engineer roles). • TypeScript-first: Next.js, React, Tailwind, Fastify, Kysely (PostgreSQL), Zod • Latest AI primitives • You don't need to know all of these, but you should be excited to learn them quickly. • How we work • These are real tradeoffs we've made, not aspirations: • Initiative-driven. We organize around customer problems, not org charts. Problems surface through product feedback, competitive analysis, and direct customer conversations — then we prioritize, build, and ship weekly. • Initiative-driven. • Customer-obsessed. We solve real problems, not hypothetical ones. Features that don't move customer metrics get cut. • Customer-obsessed. • Iterative by default. We ship small, learn fast, and never get attached to yesterday's code. This means things break sometimes — we fix forward. • Iterative by default. • AI-first leverage. We use AI to move faster and focus human time where it matters most. If a tool can do it, a person shouldn't. • AI-first leverage. • Direct feedback. We give each other actionable feedback immediately. This can feel uncomfortable — we think that's worth it. • Direct feedback. • Autonomy with accountability. We trust people to make decisions and hold them to outcomes, not process. • Autonomy with accountability.