Software Engineer, Product

Adaptyv

Greater London

On-site

GBP 70,000 - 110,000

Full time

9 days ago

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Job summary

Adaptyv in London is seeking a full-stack product engineer to build the orchestration layer of LabOS, coordinating experiment scheduling, execution, data capture and results processing. You’ll work across the stack using TypeScript, React, Node, PostgreSQL.

In a small team, you will own large areas of the product, design interfaces and APIs for scientists and AI agents, and translate goals into concrete features even when a precise spec is not provided.

Qualifications

  • Experience shipping products across the full stack.
  • Proven ability to ship, observe users, iterate and ship again.
  • Able to scope problems from goals, not a strict spec.

Responsibilities

  • Own large areas of LabOS product and orchestration layer.
  • Create interfaces and APIs for scientists and AI agents in real time.
  • Design scheduling and data flow for lab instruments and results processing.
  • Translate problems into actionable plans and features.

Skills

Full-stack production experience
Product instinct
Comfortable in ambiguity
Builds with AI
Curious about biology

Job description

Adaptyv is building an automated lab that lets AI agents run biology experiments.

We're entering the era of agentic science where AI models can now design novel proteins, propose hypotheses, and iterate on experimental results. But they can't run the experiments themselves - that's still a manual, months-long process. We're building the infrastructure that gives AI agents access to the physical world.

We are one of the fastest growing biotech companies, trusted by leading biopharmas, frontier AI labs, and the techbio companies pushing the field forward. This is a rare chance to help advance some of the most important work happening in biotech today.

Our automated lab is powered by a deep software + hardware stack: lab instruments worth millions of USD reverse-engineered into API-controllable hardware, dozens of devices orchestrated through complex workflows, full observability on everything that happens in the lab, processing pipelines for messy physical-world data, and AI systems that troubleshoot production results and accelerate assay development.

We're growing rapidly and are hiring for talented people to scale and support the massive demand for AI-driven wet lab experimentation.

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.

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