Forward Deployed Engineer

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 a scientist on staff who works shoulder-to-shoulder with customers to help them design better proteins and get more out of every experiment. You sit between their design models and our lab: helping them scope a campaign, pick the right design approach for the problem, make sense of the data that comes back, and decide what to try next. This is a hybrid role for a scientist who genuinely likes solving problems with people. One week you might be helping an AI lab choose between de novo design and a fine-tuned model for a hard target; the next, digging into a customer's binding data to work out why a design class underperformed and what to change. You'll turn one-off experiments into iterative design-build-test campaigns — and, over time, into deep, lasting partnerships. WHAT YOU'LL DO * Partner with customers to scope protein design campaigns: define the target, the success criteria, and the experimental plan to get there. * Advise on design strategy — which models and methods (de novo design, diffusion models, protein language models, structure prediction, physics-based tools) fit which problems, and where their limits are. * Help design the right experiments to test a hypothesis: what to express, what controls to include, which assays will actually answer the question. * Analyze experimental results with customers — binding, expression, stability — and translate data into the next round of designs. Deep experience with biophysical characterization techniques like SPR, BLI, nanoDSF etc is a must. * Close the loop: turn each campaign's results into sharper designs and a tighter iteration cycle. * Build trusted relationships that grow from a first project into long-term scientific partnerships. * Feed what you learn back to our product, science, and platform teams so the whole experience gets better. WHAT WE'RE LOOKING FOR * Protein science background. A degree and/or hands-on experience in protein design, computational biology, biochemistry, structural biology, or a closely related field. * Fluent in modern protein design. You understand today's design and prediction models well enough to advise on which to use when — and you keep up as the field moves. * Data-driven. You're comfortable analyzing experimental data (Python, notebooks, basic stats) and drawing clear conclusions from messy, real-world results. * Loves working with people. You're a strong communicator who's energized by solving hard problems alongside customers, not just at a desk. * Scientific problem-solver. When a campaign isn't working, you form hypotheses, design experiments to test them, and iterate — you don't guess. * Autonomous and curious. You take ownership of a customer's success and go deep on whatever the science demands. * Experience working with external partners or customers is a plus, but the core is being a great scientist who likes solving problems in the open. 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.