Product Lead, Applied AI

Lila SciencesCambridge, MA
$180,000 - $288,000Hybrid

About The Position

As the Product Manager for Software / Applied AI at Lila, you will help build the first truly AI-native system of record for scientific discovery. We are looking for product leaders who can dive deep into a specific domain and own it completely. Whether your strengths align best with our core software platform or our cutting-edge agentic science offerings, you will be embedded with a dedicated scrum team to solve complex, full-stack challenges. You will sit at the intersection of commercial, engineering, design, and scientific research, building the tools that accelerate the next generation of scientific discovery. We are hiring for a wide range of function areas, and seniority levels — final title and level will be decided at the offer stage. Priority areas include 1) data, 2) ML / computational tooling, 3) scientific agents, and 4) harness & evals.

Requirements

  • Deep Domain Ownership
  • Full-Stack Product Execution
  • The Scientific System of Record
  • Cross-Functional Orchestration

Nice To Haves

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

Responsibilities

  • Deep Domain Ownership
  • Full-Stack Product Execution
  • The Scientific System of Record
  • Cross-Functional Orchestration

Benefits

  • We offer competitive compensation including bonus potential and generous early equity.
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