Forward Deployed Scientist

Adaptyv Bio

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're the bridge between Adaptyv's lab and the people designing proteins. Protein design platforms, pharma teams, AI labs, and biotech startups all have the same problem: they can generate designs far faster than they can test them. Your job is to close that gap — to embed with a customer, understand their pipeline, and wire Adaptyv's API into their stack so that designing, building, and testing proteins becomes one continuous loop instead of a series of handoffs. This is a deeply technical, customer-facing role. You'll write real code in production systems — ours and, often, theirs. You'll go from a first integration call to a working pipeline that's submitting experiments and pulling results automatically. And you'll bring everything you learn in the field back to our product and engineering teams, so the integrations get easier every time. WHAT YOU'LL DO * Embed with customers — protein design platforms, pharma, AI labs, biotechs — to understand how they design proteins and where Adaptyv fits in their loop. * Integrate our API into their pipelines: submitting designs, tracking experiments, and pulling structured results back into their models and data stores. * Build the glue — SDKs, client libraries, scripts, and small services — that makes the integration clean, reliable, and easy to maintain. * Design the data flow between their design stack and our lab so a model's output becomes a real experiment, and real measurements flow back automatically. * Prototype quickly, then harden what works into something production-grade. * Be the technical voice of the customer internally — turn what you learn in the field into improvements to our API, docs, and product. * Help turn first integrations into durable, expanding partnerships. WHAT WE'RE LOOKING FOR * Strong software engineer. You write production code (Python and/or TypeScript), design clean APIs and integrations, and can own a system end to end. * Customer-facing instinct. You're energized by working directly with users, translating a vague need into a concrete technical plan, and shipping something they actually use. * Fast and autonomous. You parachute into an unfamiliar codebase or pipeline, figure out what matters, and get a working integration live without waiting for a spec. * AI-native builder. It's 2026 — you build with coding agents like Claude Code as a default, and you have sharp judgment about what they produce. * API and integration experience. You've built or consumed real APIs, handled auth, webhooks, retries, and messy real-world data flows between systems. * Comfortable with ambiguity. Every customer's stack is different; you like that. * Interest in biology, protein design, or ML for science is a strong plus — you don't need a bio background, but you should be excited to learn the domain and talk credibly with scientists. DETAILS * Location: Lausanne, Switzerland or remote/hybrid, occasionally travel to customers. * Type: Full time * Start date: ASAP We review applications on a rolling basis. Application deadline We are reviewing applicants on a rolling basis.

Adaptyv Bio

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 be a player-coach — someone who still ships code but also owns the engineering roadmap, team structure, and technical direction. You'll translate company strategy into engineering priorities, make sure the right things get built in the right order, and help a small, high-output team scale without losing speed. You'll lead a small, technical engineering team that leverages AI to build the software infrastructure for running our automated lab. Your job is to make it the best small engineering team in biotech, and grow it thoughtfully as we scale. This is not a management-track role where you stop building. You'll stay hands-on, especially as AI agents reshape what a small engineering team can accomplish. We expect you to be deeply technical, opinionated about architecture, and actively shipping — while also being the person who ensures the whole engineering org is pointed in the right direction and moving fast. Day-to-day, that can mean: * Owning the engineering roadmap — deciding what to build, what to defer, and what to kill * Setting technical direction and architecture across frontend, backend, data pipelines, and lab-hardware integration * Shipping code yourself on the highest-leverage problems, not just reviewing it * Hiring, growing, and setting the bar for a team that ships fast and holds quality high — our lab runs on this software, so when things break, real experiments fail and real customers are affected * Building the team's AI-assisted development practices into a genuine speed advantage WHAT WE'RE LOOKING FOR * Still building. You've shipped production software for years and you're not looking to leave the code behind — you want a role where you build and lead at the same time. * You've built teams. You've hired, managed, and developed engineers, and built a team that ships fast and holds a high bar — at least once before, in a startup or high-growth environment. * Roadmap ownership. You've owned or significantly shaped an engineering roadmap. You've made the call on what to build, defer, and kill — and you make pragmatic tradeoffs that keep things shipping and stop projects from growing out of scope. * Technical breadth. You make good architectural decisions across frontend, backend, data, and infrastructure, and you know when to go deep versus when to delegate. * AI-native. It's 2026 — you already build with AI agents and coding tools as a force multiplier, and you have a real point of view on how they change team structure, tooling, and workflow. * 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. Application deadline We are reviewing applicants on a rolling basis.

Adaptyv Bio

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. Application deadline We are reviewing applicants on a rolling basis.