Full Stack Software Engineer, Insitro

• Tenure: 2–4+ years of experience as a professional software engineer
• Engineering Fundamentals: Working knowledge of AWS or GCP, relational databases, and standard practices like version control and code review
• Product Instinct: You think like a product person — you want to know who the user is, what they're actually trying to do, and you have opinions about what to build
• Curious About the Science: You don't need a biology background, but you want to learn the domain rather than treat it as someone else's problem
• Comfortable in the Gray Area: You can reason clearly about the tradeoffs between quality and speed
• Fits the Team: You're up for writing design docs, having opinions in code review, and yes, goofing around on Slack

Desirable

• Our bar is that everything in the lab should be agentically accessible (any action a scientist can take, an agent can take), agentically legible (agents understand what the data means in insitro's context, not just how to fetch it), and humanly verifiable (a scientist can always check what an agent did and why)
• This is real robotics, workflow automation, and applied agent tooling — and your users are in the building with you
• You'll work across the stack — front end, backend, and the integrations that reach into instruments, Benchling, and agent runtimes — partnering closely with our machine learning, automation, and biology teams
• Based in South San Francisco, this role reports directly to Senior Manager, Software Engineering and offers an in-person hybrid schedule of three days per week. We'll bring you up to speed in the domain of drug development and back your ideas with real trust and mentorship along the way
• Ship Across the Stack: Build the React and TypeScript frontends scientists use every day, the Python services behind them, and integrations that reach instruments, Benchling, and agent runtimes
• Own It End to End: Take a feature from the first conversation with a scientist through the data model and UI to the alert that fires when it breaks
• Do the Normal SWE Things: Write code, review design docs, talk to users, and do code reviews that actually make the codebase better
• Agentic Tooling & Experimentation
• Chase User Appreciation: Ship things that make scientists say "OMG, this is amazing, thank you so much."
• Figure Out What's Actually Useful: Test agentic tooling ideas through prototypes, real users, and short iterative loops rather than betting on theory
• Move the Needle: Contribute work that meaningfully advances insitro's mission and the pace of drug development
• Go Watch the Work: Spend time in the lab observing the workflow before you change it
• Partner Broadly: Collaborate closely with machine learning, automation, and biology teams to build tools people actually use
• Keep Humans in the Loop: Design for provenance and verifiability, so a scientist can always check what an agent did and why