Product Engineer

Responsibilities

• Work closely with the founding team and early customers to build a world-class AI-powered product.
• Own features end-to-end — architect the backend (server logic, databases, APIs), build the frontend that exposes them, and ship to production.
• Partner with our designer and product team to translate user needs into shipped experiences — not just APIs that "the frontend team will integrate later."
• Engage in the entire application lifecycle with a high bar for coding, debugging, testing, and deploying.
• Operate as a force multiplier with AI tooling — use coding agents to move 5–10x faster than traditional engineers without sacrificing quality, and continuously evolve how our team builds, reviews, and tests software.

Role Requirements

• Enjoy working in a fast-paced environment & wear multiple hats — including ones outside your historical comfort zone.
• 2+ years of backend development experience, with demonstrated willingness (or eagerness) to own frontend work.
• You don't need to be a CSS wizard on day one, but you need to be the kind of engineer who'll learn React deeply rather than punt it to someone else.
• Experience developing products built on top of LLMs / ML.
• Proficient in Python, FastAPI, PostgreSQL, containerization and scaling microservices.
• Comfortable in (or excited to ramp on) TypeScript, React, and modern frontend tooling.
• Experience building products from zero to one.
• Able to seek & find the right resources for solving open-ended problems.
• Daily, hands-on use of modern coding harnesses (Claude Code, Codex, Cursor, or equivalent) — not as autocomplete, but as a primary way of shipping production code.
• Comfortable building and consuming MCP servers to integrate internal tools, data, and workflows into your dev loop.
• Strong point of view on AI-assisted code review, automated testing, and how to keep quality high when shipping at agent speed.
• Likely located in the San Francisco Bay Area or willing to relocate.
• BS/MS in Computer Science, Engineering, or a related technical field.

Nice-to-haves

• Experience working in a small startup environment (Seed or Series A).
• Genuine full-stack experience — comfortable across backend, frontend, and infra.
• Understand data lake / data warehouse.
• Understand Transformer / Attention / GPU inference.
• Experience with AWS, Supabase, LaunchDarkly & Betterstack.
• Built your own MCP servers, custom agents, or internal AI dev tooling.
• Published, blogged, or shared opinions about modern AI-assisted development workflows.