Product Lead, Software/Applied AI

Lila Sciences•San Francisco, MA

1d•$180,000 - $288,000•Hybrid

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. 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 introducing scientific superintelligence to solve humankind's greatest challenges, enabling scientists to bring forth solutions in human health, climate, and sustainability at a pace and scale never experienced before. Learn more about this mission at www.lila.ai If this sounds like an environment you’d love to work in, even if you only have some of the experience listed below, we encourage you to apply.

Requirements

Deep Domain Ownership: You won't be bouncing between disparate projects. 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.
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.
The Scientific System of Record: 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.
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.

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: You won't be bouncing between disparate projects. 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.
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.
The Scientific System of Record: 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.
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.