Bioengineer, Display & Library Engineering

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 are here to scale up data generation. Design teams can hand us 10⁶ sequences, and our automated infrastructure measures on the order of 10³ of them individually. Library construction and display is what closes that gap. We want someone who has set these systems up before and can do it again here, with their own hands. Phage, ribosome, mRNA, yeast, cell-free: which one fits depends on the library and the target, and part of the job is making that call and then building it rather than writing a recommendation. This is a build role, not a service role. For your first months you are making libraries, running selections, working out why a round collapsed, and turning what works into something the automation team can run without you. What You'll Do Build the libraries. Oligo pools, combinatorial assembly, barcoding. More campaigns fail here than at selection. Run selections end to end , including the call on whether a round enriched real binders or just fast growers. Pick the platform per campaign and stand it up. Based on the library and the target, not on what you happened to use last. Own the sequencing analysis. You don't need to be a bioinformatician, but you can't be waiting on one. Hand off to automation. A protocol that only works when you personally run it isn't finished. Close the loop. Selected designs get expressed and measured on BLI and SPR by the team next door. That tells you whether the selection worked. What We're Looking For MSc / PhD in molecular biology, protein engineering, or a relevant field, plus 3+ years running display and selection yourself. You have set up a display platform, not just used one. This is the core requirement. Built the library, got the selection working, and produced binders that held up in an independent assay