This is a hands-on full-stack engineering role where one person owns big pieces of an internal platform that runs a physical lab. The work spans scheduling experiments, controlling instruments through software, and showing live lab status to scientists and AI agents. A strong candidate has shipped production web products, can turn a loose goal into a plan, and cares about what users actually do with the product.
How it fits the AI era
AI agents are becoming the main users of this software, so the work includes building tools that let them request experiments, read results and help fix failed runs. AI coding tools are expected in daily work, though the person still needs enough experience to judge whether the output is good. What stays human is deciding what to build, handling messy real-world edge cases, and making sure a physical lab runs safely and reliably.
How it builds AI experience
Someone in this role would gain experience building agents that make decisions across a real experiment cycle, from planning a protocol to troubleshooting results. They would also learn how AI-designed proteins are tested in practice, since the lab turns digital sequences into measured data. To prepare, a candidate could build a small agent project that calls an API, handles failures and logs what it does, and read up on how protein assays work.
Worth showing
- Full-stack TypeScript and React
- Shipped and iterated on a product
- Building AI agents and tooling
- Scoping vague problems into plans
This is our own read, written from the employer’s posting and the company’s Spotlight. The employer’s posting is the source of truth for the role.
About Adaptyv Bio
An automated lab that tests AI-designed proteins, so researchers can send a sequence and get real experimental data back.
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