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 roleYou’ll build backend systems that make our lab programmable. You'll architect data pipelines that process large-scale protein characterization data, build APIs that integrate laboratory instruments and robotics into our software stack, and work closely with scientists and automation engineers to translate complex molecular biology workflows into reliable, scalable software. This is not SaaS slop, you're making physical machines do precise biology with minimal human intervention.
What we're looking for
Strong experience designing and building production backend systems. We use Python and TypeScript on the backend with Postgres, but what matters is that you can architect systems that are reliable and maintainable.
Experience building data pipelines and processing infrastructure. You'll be handling large volumes of heterogeneous data from physical instruments such as binding kinetics data, enzyme activity measurements, chromatography readings, and turning them into clean, structured datasets.
Comfortable with API design and systems integration. A big part of this role is making hardware talk to software: connecting instruments, robotics, and scheduling systems into a coherent whole.
A genuine interest in biology. No background required, but our product is running biology experiments in the physical world and that should excite you.
High-autonomy, founder mindset. We share context and vision openly. You figure out what matters most and go work on it.
Pragmatism. You care about solving the problem well, not about the stack or the tools.
You write code primarily with AI, but you have enough experience writing software without it to know what good code and good architecture look like.
Application deadline
We are reviewing applicants on a rolling basis.
