Technical Program Manager, Foundation Models (Staff / Principal)

About the Team
Join a world-class team at the forefront of AI and biochemistry.
At Genesis Therapeutics, we’re a tight-knit team of proven deep learning researchers, software engineers, and drug discovery pioneers. Our shared mission is nothing short of revolutionary: to forge the next generation of AI foundation models that will unlock groundbreaking therapies for patients with severe diseases.
We don’t just apply machine learning to biology; we are conducting fundamental research at the intersection of machine learning, physics, and computational chemistry, pushing the boundaries of each field. You will work side-by-side with top multidisciplinary researchers to design and build generative foundation models at scale, having access to ample compute and large-scale simulations.
About the RoleAs the Technical Program Manager for our Genesis AI team, you will be the operational leader orchestrating our most critical scientific and engineering initiatives. Your core mission is to drive the end-to-end delivery of our foundation models, ensuring our ambitious research roadmap translates into tangible, high-impact models that power our drug discovery platform.
You will be the nexus of our technical operations, creating the systems and processes that allow our research to scale effectively. You will ensure that our machine learning-led drug discovery programs are delivered on-time, on-scope, and aligned with scientific milestones. You will also help define and mature program processes, experiment governance, and model deployment pipelines that support our scientific mission. This means owning the strategic planning for our large-scale compute resources, implementing rigorous configuration management for reproducible research, and building the connective tissue between our AI researchers, platform engineers, and drug discovery teams.

You Will

• Orchestrate the end-to-end delivery of our foundation models, translating strategic research goals into executable roadmaps and concrete milestones.
• Manage our large-scale compute resources, partnering with research and engineering leads to ensure efficient scheduling and allocation for our most critical experiments.
• Implement and oversee configuration management, establishing best practices for experiments, data, and models to ensure research is reproducible, traceable, and robust.
• Drive cross-functional execution and mitigate risk by proactively identifying dependencies, anticipating blockers, and ensuring clear communication across all teams.
• Design and mature our operational processes, creating lightweight, effective systems for experiment tracking, project documentation, and model release governance.
• Act as a central communication hub, ensuring stakeholders from the AI team, the drug discovery labs, and leadership are aligned and informed.

You Are

• A seasoned Technical Program Manager with significant experience managing complex ML, scientific computing, or biotech-focused projects.
• A deeply technical partner whose background allows you to communicate fluently with ML researchers, platform engineers, and computational chemists.
• An expert at navigating research-driven ambiguity, skilled at bringing structure, clarity, and focus to open-ended scientific projects, aligning priorities across science and engineering.
• A master of execution and organization, able to translate high-level strategy into detailed plans and manage multiple concurrent workstreams flawlessly.
• An exceptional communicator and collaborator who excels at building consensus and aligning technical and non-technical partners toward a common goal.
• Passionate about advancing science through technology in high-impact, mission-driven work.
• Inspired by our culture of intellectual curiosity and the shared belief that breakthroughs happen when diverse perspectives and minds unite.

Nice to Haves

• A BS or higher in Computer Science, Computational Chemistry, BioEngineering or a related field.
• Experience at an early-stage biotech or AI startup.
• Familiarity with small molecule drug discovery: cheminformatics, molecular property modeling, or structure-based design.
• Hands-on experience with tools like Asana, Notion, GitHub, Weights & Biases, or similar experiment tracking and project management platforms.