Product Lead, Software/applied AI

Lila Sciences Lila Sciences · AI Frontier · One Charles Park, Cambridge, MA +1 · Corporate Development

Product Lead for an AI-native system of record for scientific discovery, focusing on building tools that accelerate scientific research. The role involves deep domain ownership, full-stack product execution, and cross-functional orchestration between research and engineering teams. Priority areas include data, ML/computational tooling, scientific agents, and harness & evals. Requires strong product management experience in complex B2B SaaS or technical platforms, comfort with ambiguity, and a bias for action. Scientific background and experience building for scientists are preferred.

What you'd actually do

  1. Deep Domain Ownership: We will match your unique product strengths to a specific scrum team, where you will go deep, define the roadmap, and become the absolute subject matter expert for that product area. That said, we operate as one product team and collaborate closely.
  2. Full-Stack Product Execution: From designing user-facing scientific workflow tools to shaping the underlying data infrastructure that powers our AI models, you will define requirements and guide execution across the entire stack.
  3. The intelligence platform for Science: Build intuitive, powerful software that scientists actually want to use. You will be responsible for translating incredibly complex scientific workflows into scalable, elegant digital products.
  4. Cross-Functional Orchestration: Lead the dialogue between our research scientists (who push the boundaries of what's possible) and our engineering teams (who build robust, scalable systems), ensuring we ship high-impact, cohesive products.

Skills

Required

  • Product Management experience building complex B2B SaaS, data-heavy platforms, or highly technical software products
  • comfortable navigating both the user experience of a complex workflow and the technical realities of the backend architecture required to support it
  • thrive in ambiguous environments
  • take a vague, highly technical customer request and turn it into a clear, prioritized roadmap for your engineering team in days, not weeks
  • care deeply about the "how" — how the product is built, how it performs, and how it directly impacts the end user's daily work

Nice to have

  • Scientific Background: A degree or deep practical experience in the hard sciences (materials science, chemistry, biology, etc.)
  • Building for Scientists: Direct experience building software, tools, or platforms specifically designed for scientific researchers or lab environments
  • Startup DNA: Experience as an early-stage product manager who knows how to move fast, iterate, and build from 0 to 1

What the JD emphasized

  • scientific agents
  • harness & evals
  • scientific workflows
  • AI models
  • scientific discovery
  • AI-native system of record
  • scientific Superintelligence

Other signals

  • AI-native system of record for scientific discovery
  • embedded with a dedicated scrum team
  • solve complex, full-stack challenges
  • intersection of commercial, engineering, design, and scientific research
  • building the tools that accelerate the next generation of scientific discovery
  • Priority areas include 1) data, 2) ML / computational tooling, 3) scientific agents, and 4) harness & evals
  • define the roadmap, and become the absolute subject matter expert for that product area
  • From designing user-facing scientific workflow tools to shaping the underlying data infrastructure that powers our AI models
  • define requirements and guide execution across the entire stack
  • Build intuitive, powerful software that scientists actually want to use
  • translating incredibly complex scientific workflows into scalable, elegant digital products
  • Lead the dialogue between our research scientists (who push the boundaries of what's possible) and our engineering teams (who build robust, scalable systems)
  • ensuring we ship high-impact, cohesive products
  • Product Management experience building complex B2B SaaS, data-heavy platforms, or highly technical software products
  • comfortable navigating both the user experience of a complex workflow and the technical realities of the backend architecture required to support it
  • thrive in ambiguous environments
  • take a vague, highly technical customer request and turn it into a clear, prioritized roadmap for your engineering team in days, not weeks
  • care deeply about the "how" — how the product is built, how it performs, and how it directly impacts the end user's daily work
  • Scientific Background: A degree or deep practical experience in the hard sciences (materials science, chemistry, biology, etc.)
  • Building for Scientists: Direct experience building software, tools, or platforms specifically designed for scientific researchers or lab environments
  • Startup DNA: Experience as an early-stage product manager who knows how to move fast, iterate, and build from 0 to 1
  • Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges
  • science is the most inspiring frontier for AI
  • Rather than hard-coding expert knowledge into tools, LILA builds systems that can learn for themselves
  • LILA combines advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science that executes the entire scientific method autonomously, accelerating discovery at unprecedented speed, scale, and impact across medicine, materials, and energy