Product Engineer, Products

Build something that did not exist last month. Then own what happens when customers use it.

New products at Metaview do not live in an innovation lab. They start with a real customer problem and become production software with the same person responsible from first idea through adoption, failure, and revision.

You will work without a fixed roadmap. You will talk to users, find the product insight, prove it through working software, and turn the first useful version into something customers can trust.

This is not an incubation role that hands prototypes to another team. It is the same product-engineering remit, entered through zero-to-one work. Engineers move between new capabilities and the products they grow into.

Metaview is an applied AI lab building AI coworkers for some of the world’s most ambitious recruiting teams. Hear directly from our customers. The challenge is not another chatbot. It is software that can pursue a hiring objective, act across real workflows, ask for judgment at the right moment, and earn a customer’s trust.

Founded by Siadhal Magos and Shahriar Tajbakhsh, who scaled Uber and Palantir, we have raised more than $50M and are growing 5x year over year.

AI coding agents are part of the job, not a perk. Engineers routinely run several in parallel for exploration, implementation, and review. We assess both sides of the craft: how well you direct agents and how well you reason, code, and debug on your own. One interview exercise is completed without AI.

Velocity means reducing the time from customer evidence to a reliable product change. It does not mean trading away quality. We ship small changes daily, including Fridays, because the engineer who ships owns production behavior, recovery, and the next revision. Process stays light because customer context and ownership are direct.

The goal is not to produce prototypes quickly. It is to discover the right product quickly. You will launch early enough to learn, then stay with the work until the behavior, interface, reliability, and adoption are strong.

AI agents help our small team ship roughly 8x more product changes than a year ago. The engineer remains accountable for architecture, review, implementation quality, and production behavior.

You will work on problems such as:

• building agents that can pursue recruiting objectives over days, know when to ask for judgment, and recover safely when a model or tool fails;

• turning interview and hiring-team conversations into actions, with interfaces that let recruiters understand, correct, and trust the result;

• finding simple product primitives that unlock broad recruiting workflows;

• building the interface, APIs, data model, permissions, and production behavior of a new customer workflow; and

• turning customer behavior into a sharper product opinion and a better next release.

In your first 3 to 6 months, you should independently own and ship a bounded customer outcome from problem definition through rollout and iteration. The size of that outcome will reflect your level, but the operating model is the same: make product and technical decisions, contribute the consequential code, and own the production result.

• 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…