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Metaview is an applied AI lab building AI coworkers for recruiting teams. Founded by alumni from Uber and Palantir, the company has raised $50M+ and is growing 5x year-over-year. This is a hands-on product engineering role where you own customer outcomes end-to-end: from problem definition through implementation, production launch, and iteration.
You will work on problems including: building AI agents that pursue recruiting objectives over extended workflows while knowing when to request human judgment and recovering safely from model or tool failures; turning interview and hiring conversations into actionable workflows with interfaces that let recruiters understand and trust the results; making architectural tradeoffs across interfaces, APIs, data models, permissions, and production behavior; designing controls and recovery paths for agents acting in customer systems; and turning repeated patterns into simple primitives supporting many workflows.
The role spans mid-level and staff+ scope under the same hands-on operating model. At mid-level, you independently own a bounded customer outcome across product and implementation. At staff+, you still write code while setting direction for a broader area, making hard architectural tradeoffs, and raising decision quality around you. Leveling is based on demonstrated scope, not tenure.
Metaview's operating value is velocity: reducing time from customer evidence to reliable product change without trading away quality. Engineers ship small changes daily, including Fridays. The engineer who ships owns production behavior, recovery, and the next revision. Process stays light because customer context and ownership are direct. You won't wait for complete specifications or handoffs between disciplines—you get close to the customer, choose a direction, build the consequential layers, and use production behavior to decide next steps.
AI coding agents are part of the job, not a perk. Engineers routinely run several in parallel for exploration, implementation, and review. The company assesses both sides of craft: how well you direct agents and how well you reason, code, and debug independently. One interview exercise is completed without AI assistance.
In your first 3–6 months, you should independently own and ship a bounded customer outcome. The size reflects your level, but the operating model is consistent: make product and technical decisions, contribute consequential code, and own the production result.
The tech stack includes React, TypeScript, Python, AWS, Postgres, and S3. Experience with these exact technologies is not required.
This is a hands-on product IC role, not a people-management or model-research position. You will work in-person in San Francisco; this is not a remote role with occasional office attendance. Decisions are made by people closest to the customer and the code.
REQUIREMENTS:
- You have personally shipped software for external users and owned a meaningful outcome from problem definition through production.
- You have real depth in at least one technical area and can cross product, frontend, and backend boundaries when the outcome requires it.
- You use AI coding agents heavily and can still design, implement, review, and debug independently.
- You want direct customer contact, hands-on implementation, and responsibility after launch.
- You care deeply about architecture, correctness, and technical craft, but judge them by the product they enable.
- You want product judgment to be part of software engineering, not something delivered through a roadmap.
