Software Engineer, Product

Adaptyv Bio; Vaud; Hybrid; CHF 120,000 - 180,000; Full time

Job summary

Adaptyv Bio is hiring a full-stack product engineer for LabOS, building orchestration across experiment scheduling, execution, and data processing. You will create APIs and interfaces that give scientists and AI agents real-time lab visibility and build AI-driven tooling for protocol design and troubleshooting.

You will turn proprietary hardware into API-controllable devices and design scheduling systems for dozens of lab instruments, shaping large product areas in a small team with high impact.

Qualifications

• Five bullets describe soft skills and mindset: strong full-stack production experience across modern JS stack, product intuition with shipping ownership, comfort in ambiguity and independent planning, familiarity with AI tools and evaluating output quality, and genuine curiosity about biology and running experiments.

Responsibilities

• Build the orchestration layer for experiment scheduling, execution, and data capture.
• Create interfaces and APIs for real-time visibility into lab activities for scientists and AI agents.
• Develop AI agents and tooling to automate decisions across the experiment lifecycle.
• Turn hardware into API-controllable devices for programmatic operation by agents and software.
• Design scheduling systems coordinating multiple lab instruments with complex dependencies.

Skills

Full-stack development

Product intuition

Ambiguity tolerance

AI tooling experience

Biology curiosity

Tools

TypeScript

React

Node

Postgres

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.