Director of Product, Life Sciences
Lila SciencesCambridge, MA USAPosted 26 March 2026
Tech Stack
Job Description
Your Impact at Lila
Lila Sciences is looking for a Director of Product, Life Sciences strategic and visionary product leader who will shape the future of our therapeutic research and development capabilities. Reporting to the Vice President, Life Science Product, you will lead the strategy, roadmap, and execution for products and platforms at the intersection of drug discovery, chemical synthesis, and scientific intelligence.
What You'll Be Building
Drive the strategic direction for turning our AI capabilities toward breakthrough solutions in drug discovery, chemical synthesis, and molecular characterization
Translate strategic objectives into target product profiles (TPPs) and development campaigns that guide science and engineering teams and enable breakthrough innovations in life sciences
Lead customer and internal-user discovery, serving as the technical link to external customers and partners in the life sciences
Identify and shape product opportunities grounded in real-world discovery challenges, partnering closely with collaborators, customers, and strategic partners to ensure relevance and downstream value
Translate insights into clear product requirements, acceptance criteria, and experiment plans that guide engineering and science teams
Drive product execution from concept to launch while leading cross-functional teams across science, machine learning, automation, and software engineering
Manage resource allocations (budget, compute, lab access, people) and decisions against a complex set of priorities (e.g., focus of experiments between AI model training and near-term partnership requests)
Define clear success metrics and milestones, and clearly communicate progress against them to the company, including executive leadership
What You’ll Need to Succeed
MS, PhD, or equivalent experience in medicinal chemistry, chemical biology, chemical engineering, biochemistry, or a related field, with a strong grounding in experimental science
7+ years in Product Management building new and/or experimental products in drug discovery, molecular profiling, machine learning, or scientific software development
Deep understanding of drug development processes, molecular and cellular research tools, and wet and dry lab workflows
Experience with small molecule discovery workflows (e.g., lead optimization, ADMET profiling, synthesis planning) is strongly preferred
Experience defining and executing target product profiles (TPPs) for new drug products, life sciences research tools, or scientific data platforms
Experience with managing extremely complex, multidisciplinary projects using project management best practices
Relentlessly output-focused; driven by impact against our mission and program goals, not by doing tasks, owning decisions, or being in meetings
Proven ability to influence without authority and lead cross-functional teams effectively
Highly collaborative and empathetic
High degree of comfort with ambiguity and able to adapt to changing teams and needs
Able to create small, achievable units of work from large, complex, and ambiguous goals
Excellent communication and presentation skills, capable of conveying technical information to any audience
Bonus Points For
Experience with automated/self-driving labs and experience working with (not necessarily having run) ML approaches relevant to drug discovery and molecular science
Following the rapid evolution of LLMs and other AI solutions and have thoughts and opinions on how this will impact the future of scientific discovery and product development
Background in partnering with biopharma or research organizations to define collaborative milestones and workflows
About Lila
Lila Sciences is the world’s first scientific superintelligence platform and autonomous lab for life, chemistry, and materials science. We are pioneering a new age of boundless discovery by building the capabilities to apply AI to every aspect of the scientific method. We are intro ... (truncated, view full listing at source)
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