Life Science Program Lead, AISF
Lila SciencesCambridge, MA USAPosted 28 April 2026
Job Description
Your Impact at LILA
We are looking for a Program Lead to own the strategy and execution of our Life Science artificial intelligence science factory (AISF) Program. This is a single-point-of-accountability role: you will design and execute a plan that is maximally responsive to the priorities of the Product, Revenue, and Science teams while leveraging and extending the Lila tech stack. Success requires deep collaboration with stakeholders, representation of the strategy to the executive team, and driving progress via delegative leadership, where cross-functional Project Teams execute the strategy via our team-of-teams operating model.
Life Science AISFs span capabilities in cell biology, protein science, nucleic acid science, small molecule therapeutics, and targeted delivery — the experimental backbone that enables our AI to learn from biology at scale. This role sits at the intersection of deep domain expertise and strategic platform development, making it one of the most technically consequential leadership positions at Lila.
What You'll Be Building
Program Ownership
Define the "How and When" in response to strategic "What and Why" inputs from Product, Science, and AI teams
Propose, negotiate, and own Program Charters for Life Science AISFs, including scope, budget, timeline, and success criteria
Collaborate with Finance to dynamically manage program budget and strategy throughout execution, escalating or reallocating as needed
Technical Leadership
Architect the strategy for expanding Life Science AISF capabilities across cell, protein, nucleic acid, small molecule screening, and delivery experimental platforms, in close coordination with the Product, AISF Engineering, Software, Robotics, and Life Science Experiment teams
Evaluate proof-of-concept results from frontier Science Programs (e.g., Autoimmunity, Solid Tumor, Protein Persistence), align with Product on their value creation potential, and design their integration into the Life Science AISF platform
Ensure new platform capabilities are well-scoped, derisked, and positioned to accelerate downstream Intelligence Programs
Maintain and extend Lila's best-in-world autonomous science platform for life sciences
Design the Life Science AISF to be a maximally expressive lab with unprecedented responsiveness to AI guidance
Team and Execution Management
Form and advise Life Science Project Teams; ensure teams have the resources, clarity, and support to execute autnomously
Coordinate with Science Program Leads whose work depends on Life Science AISF capabilities
Resolve resourcing conflicts within your program via collaboration with Product; escalate to senior leadership when a solution aligned to the approved charters cannot be identified
Stakeholder Communication
Represent Life Science AISF programs in Technical Leadership Team (TLT) reviews
Communicate program status, risks, and strategic decisions to TLT and cross-functional partners
What You’ll Need to Succeed
PhD or equivalent experience in a life sciences discipline (cell biology, biochemistry, molecular biology, or related field), with substantial postdoctoral or industry research experience
Track record of leading complex, multi-disciplinary experiment and lab automation programs
Familiarity across multiple Life Science AISF domains (cell-based assays, protein characterization, nucleic acid workflows, or delivery systems)
Experience with autonomous experiment platforms
Experience defining and managing technical roadmaps with resource and timeline constraints
Strong written and verbal communication, coupled with the ability to translate technical depth into strategic clarity for diverse audiences
Bonus Points For
Familiarity with AI/ML-driven experimental design or closed-loop science workflows
Prior experience in a fast-paced, technology-driven research environment (biotech, pharma, or deep-tech startup)
Experience working in a matrixed organization with shared resources across multiple co ... (truncated, view full listing at source)
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