Duvo Inc - Tech Lead

• These are non-negotiables—the things we'll specifically evaluate you on: • Shipping and ownership. You've repeatedly taken ambiguous problems to production with measurable outcomes. You own features end-to-end: UI → API → data → deployment. • Technical leadership. You make architecture decisions, manage tech-debt tradeoffs, and set quality standards. Your team trusts your judgment because you're in the codebase with them. • AI/ML product literacy. You have hands-on experience building with LLMs, retrieval systems, or evaluation harnesses. You understand the primitives well enough to make sound build-vs-integrate decisions and catch failure modes. • Product judgment. You can define MVP scope, pick the right metric to move, and kill work that isn't delivering value. You connect technical choices to customer outcomes, not just technical elegance. • People management. You run 1:1s, give direct feedback, support career development, and hire well. Your management style is shoulder-to-shoulder, not top-down. Part of your job is developing engineers on your team into future technical leaders. • Judgment under pressure. You'll decide build-vs-buy, choose between shipping fast and shipping right, and make architecture calls that affect the whole platform — often without complete information. • Have a strong sense for security and reliability in production AI systems. • Have excellent UI/UX taste and an eye for detail — our product is the interface between enterprises and AI agents, and craft matters. • Be a full-stack generalist who thrives on new problems and ambiguity. • Have designed and operated distributed systems at scale. • Have deep applied LLM experience — evaluation design, prompt engineering, safety controls, and cost optimization in production. • This is not for you if • You want a pure management role without writing code — see Engineering Manager. • You see management as career advancement rather than a way to multiply your team's impact. • TypeScript-first • React and Fastify • Latest AI primitives • 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. • Customer-obsessed. We solve real problems, not hypothetical ones. Features that don't move customer metrics get cut. • Iterative by default. We ship small, learn fast, and never get attached to yesterday's code. This means things break sometimes — we fix forward. • 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. • Direct feedback. We give each other actionable feedback immediately. This can feel uncomfortable — we think that's worth it. • Autonomy with accountability. We trust people to make decisions and hold them to outcomes, not process.