Software Engineer, Lab Automation

<p style="min-height:1.5em"><strong>Adaptyv is building an automated lab that lets AI agents run biology experiments. </strong></p><p style="min-height:1.5em">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.</p><p style="min-height:1.5em">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.</p><p style="min-height:1.5em">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.</p><p style="min-height:1.5em">We’re growing rapidly and are hiring for talented people to scale and support the massive demand for AI-driven wet lab experimentation.</p><h2>About the Role</h2><p style="min-height:1.5em">You'll build work-cell orchestration, instrument drivers, protocol scheduling, error-recovery logic, and monitoring. Physical systems fail in ways pure software doesn't — a plate gets stuck, a liquid handler skips a well, a temperature controller drifts. Your job is to make the system handle all of it gracefully. This is a broad, hands-on role for a strong engineer who wants their code to drive real machines and see it run the same day.</p><h2>What You'll Do</h2><ul style="min-height:1.5em"><li><p style="min-height:1.5em">Build orchestration software that coordinates liquid handlers, plate readers, incubators, and robot arms — handling timing dependencies, state, and error recovery.</p></li><li><p style="min-height:1.5em">Reverse-engineer and develop instrument drivers and APIs. Each instrument speaks a different protocol (serial, USB, TCP/IP); you work out how it talks and build a clean abstraction over it.</p></li><li><p style="min-height:1.5em">Model and execute complex multi-step protocols reliably — a single run can span dozens of steps across multiple instruments.</p></li><li><p style="min-height:1.5em">Build error-recovery logic so that when something fails mid-run, the system retries, skips, alerts, or pauses depending on the failure mode.</p></li><li><p style="min-height:1.5em">Create monitoring and observability for work-cell health: instrument status, run progress, error rates.</p></li><li><p style="min-height:1.5em">Debug across the software–hardware boundary — figuring out whether bad data is a comms, firmware, calibration, or code problem.</p></li><li><p style="min-height:1.5em">Work closely with lab automation engineers, the rest of the software team, and the scientists running production.</p></li></ul><h2>Stack</h2><p style="min-height:1.5em">TypeScript and Python, Postgres (Supabase), Modal for compute. We control instruments with open-source Python tooling like <strong>PyLabRobot</strong> and <strong>PyHamilton</strong> wherever we can, rather than proprietary vendor GUIs.</p><h2>What We're Looking For</h2><ul style=&q