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. Coding was first. Recruiting is next. We are building it. Metaview is an applied AI lab building AI coworkers for some of the world’s most ambitious recruiting teams. 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. Our operating value is velocity. 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.
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Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed