Bioengineer

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

This is a hands-on research role in our biology and production team. You'll work on the science that underpins everything Adaptyv does: developing and optimizing protein expression systems, running molecular biology workflows, and pushing the boundaries of what we can produce and characterize at scale.

We express proteins at high volume across cell-free and cell-based systems, run DNA synthesis and assembly at high throughput, and characterize binding, stability, and function using BLI, SPR, and enzymatic assays.

What you'll do

• Develop and optimize protein expression workflows - cell-free expression (PURE, lysate-based), E. coli, and potentially mammalian systems. Troubleshoot when proteins don't express, misfold, or aggregate.

• Design and execute DNA synthesis and assembly protocols: PCR, Golden Gate, Gibson. Improve yield, fidelity, and throughput.

• Develop new assays or adapt existing ones for the platform - thermostability, developability, enzyme activity, or whatever the next customer need demands.

• Run experiments yourself. This is not a project management role. You'll be at the bench doing molecular biology, analyzing data, and iterating on protocols.

• Work with the automation team to translate your methods into automated workflows. You develop the protocol that works; they make the robots run it.

• Analyze experimental data, identify failure modes, and improve methods systematically. When 20% of constructs in a batch fail to express, you figure out why.