Vice President of Engineering, Formation Bio

• An AI-native point of view. You have hands-on experience shipping LLM- or agent-powered systems that own meaningful workflows in production, and you have a clear perspective on how AI is reshaping the role of the engineer and the shape of engineering teams over the next few years
• 10+ years across software and data engineering, with meaningful time as a hands-on builder before stepping into leadership, and a track record managing 15+ engineers in technical, interdisciplinary settings
• A driver's posture. You shape the agenda rather than wait for it. You reason from first principles, push back constructively on the leadership team, and bring an opinion about where engineering should go next
• Mission alignment. You care about solving the drug-development bottleneck and want your engineering work to compound into better outcomes for patients

Desirable

• We're looking for a Vice President of Engineering to lead and grow the team that builds the AI-native software platform behind our drug development engine. Reporting to the CTO, you'll partner closely with leaders across Clinical, R&D, BD, and Data Science to translate hard biological and operational problems into computational leverage
• This is a builder's seat. We're past the era where AI is something you bolt on to engineering — we're actively rethinking how teams are shaped, how work flows, and how engineers spend their time when agents handle a meaningful share of the build. We want a leader who is excited to do that rethinking with us, not someone looking for the next predictable VP step
• Set the technical vision for an engineering organization that prioritizes high-leverage computational capability over feature factories
• Design and evolve how the team uses agents, MCP-based tool orchestration, and LLM-integrated systems — not just for developer productivity, but as a fundamental shift in how engineering work gets done
• Partner with the CTO, Data Science, and the broader leadership team to translate clinical and BD bottlenecks into engineering bets that move asset value
• Ship LLM-integrated features and autonomous agents into production in support of R&D, clinical operations, and trial execution
• Build platforms for ingesting and operationalizing complex external, clinical, and biological datasets — the foundation our Data Science partners rely on
• Embed engineers inside Business Development, Clinical, and R&D so technology partners with the science from the start
• Own GxP-validated clinical environments and automated security and compliance — making rigor a property of the platform rather than a checkpoint
• Hire, mentor, and shape an engineering organization of 15+ with high talent density, refactoring team structure as the work itself evolves