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Software Engineer, Product

Adaptyv
London, GBR
Full-time
Mid
Onsite
Discovered 5 days ago
typescript

Full Job Posting

About the role

You'll work across LabOS — our internal software platform — building the orchestration layer that coordinates everything from experiment scheduling to execution to data capture and results processing. This is full-stack product engineering at the intersection of software and physical-world biology.

Day-to-day, that can mean things like:

Creating interfaces and APIs that give scientists and AI agents visibility into what's happening in the lab in real time

Building custom AI agents and tooling that automate decisions across the experiment lifecycle, from protocol design to troubleshooting failed results

Turning proprietary hardware into API-controllable devices that agents and software can operate programmatically

Designing scheduling systems that coordinate dozens of lab instruments with complex dependency chains

You'll own large areas of the product. We're a small team where individual engineers have large impact on what gets built and how.

What we're looking for

Full-stack production experience. We use TypeScript, React, Node, Postgres, but what matters is you can work across the stack.

Product instinct. You've shipped, watched users, iterated, and shipped again.

Comfortable in ambiguity. You start from a goal, not a spec. You scope problems down, decide what to build and what to skip, and write your own plan when none exists.

Builds with AI. You use AI tools heavily, but you have enough experience without them to know what good looks like.

Curious about biology. No background required, but running real experiments in the physical world should excite you.

Application deadline

We are reviewing applicants on a rolling basis.

Qualifications

  • Full-stack production experience. We use TypeScript, React, Node, Postgres, but what matters is you can work across the stack.
  • Product instinct. You've shipped, watched users, iterated, and shipped again.
  • Comfortable in ambiguity. You start from a goal, not a spec. You scope problems down, decide what to build and what to skip, and write your own plan when none exists.
  • Builds with AI. You use AI tools heavily, but you have enough experience without them to know what good looks like.
  • Curious about biology. No background required, but running real experiments in the physical world should excite you.
  • Application deadline
  • We are reviewing applicants on a rolling basis.

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