Senior / Principal Technical Program Manager, Life Sciences AI

Your Impact at LILA

Lila is building a platform where AI and automation co-evolve to solve the hardest problems in medicine. Within Life Science AI (LSAI), Lila develops large-scale generative models and reasoning frameworks — spanning biological sequences, molecular structures, and multimodal experimental data — that power automated scientific discovery and feed Lila's closed-loop "Lab-in-the-Loop" discovery engine. As that work scales, the surface area of cross-functional coordination across model research, evaluation, experimental science, and downstream integration is growing fast.

We are looking for a Senior or Principal Technical Program Manager to join our AI Research team and bring structure, accountability, and delivery cadence to Life Sciences AI. You will be the connective tissue between model researchers, computational and wet-lab scientists, automation and software teams, and the broader Lila organization. The successful candidate thrives in ambiguity, communicates exceptionally well across audiences, and knows how to build clarity and momentum on a fast-paced, rapidly scaling team. In addition, you must be genuinely curious about how foundation models for biology drive scientific discovery and able to clearly articulate what each program is trying to deliver.

What You'll Be Building

• Establish and operate the delivery cadence and rhythm for the Life Sciences AI organization — driving program planning, status, milestone tracking, and risk management across foundation model research, evaluation, and integration with Lila's closed-loop discovery engine.
• Serve as the key communication interface between LSAI and partner organizations (model training, experimental science, automation, software, product, and leadership); set up the organizational information flows that allow this communication to happen with speed at scale.
• Drive accountability across distributed, cross-functional teams without relying on direct authority; build consensus through clear communication and sound judgment.
• Translate research priorities into structured, accountable program execution: define workstreams, milestones, dependencies, and risks across biological sequence design, structure prediction, multimodal scientific reasoning, and other LSAI program areas.
• Partner with experimental scientists and computational biologists to keep the Lab-in-the-Loop feedback cycle on schedule — ensuring data generation, model training, and experimental validation stay synchronized.
• Implement best practices for rapid experimentation and iteration, enabling new LSAI workstreams to ramp efficiently as the team grows.
• Develop clear documentation and reporting to communicate vision, track progress, and align LSAI work with broader AI Research and company-wide priorities; represent program status and risks accurately even when the picture is uncertain or evolving.

What You'll Need to Succeed

• Bachelor's or Master's degree in Computer Science, Engineering, Life Sciences, or a related field.
• 8+ years of program or project management experience in technology, AI/ML, or life sciences environments.
• Proven experience leading cross-functional programs and driving them to successful completion under tight delivery timelines.
• Strong analytical and problem-solving skills, with the ability to turn technical and scientific requirements into actionable program roadmaps.
• Track record of driving accountability without direct authority across engineering, research, and scientific stakeholders.
• Exceptional written and verbal communication skills; track record of producing executive-quality documents, roadmaps, and updates that drive decisions.

Bonus Points For

• Direct experience in AI/ML research or product organizations, ideally in a program management or research operations capacity.
• Working familiarity with foundation models, generative AI, or ML for biology — sufficient to engage credibly with researchers and ask good questions.
• Exposure to experimental science workflows or closed-loop discovery systems where computational and wet-lab work iterate together.
• Experience managing programs that span research, evaluation, and integration workstreams in fast-moving technical environments.
• Enthusiastic about emerging technologies and experienced in driving rapid experimentation and program iteration.