Product Manager

United States·New YorkFull Timemid

Product ManagementProduct Manager

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Quick Summary

Key Responsibilities

Experience with scientific, laboratory, robotics, or industrial software Familiarity with AI/ML products, LLM-based systems,

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Product ManagementProduct Manager

Radical AI is replacing an R&D process that currently takes 10+ years and $100 million to produce a single discovery. Our self-driving lab platform combines AI with autonomous robotics to run experiments, analyze results, and iterate—continuously, without human bottlenecks. For industries like aerospace, automotive, defense, energy, manufacturing, semiconductors, and space, that means breakthroughs in weeks instead of years.

We're looking for a Product Manager to own the software platform and agent layer at the core of what we build. This is a focused, high-leverage scope in a company where the product is genuinely novel — there's no established PM playbook for an AI-driven autonomous materials lab, and we're not looking for someone to follow one.

You'll report to our President and Co-founder and work directly with scientists and engineers building systems without obvious analogs. In a company this size, that means being in the room for conversations that actually shape what gets built. Those conversations are substantive and sometimes contentious — this is a team with strong opinions and the technical depth to back them up.

This is not a coordination role. We're looking for someone who drives product thinking — develops sharp intuitions about what matters, translates those into clear requirements, and holds the thread from discovery through delivery. That means being willing to defend a product position when engineers push back, knowing when to stand firm and when to update your view, and earning credibility through judgment rather than authority. It also means getting close to customers — understanding their problems well enough to define the right solutions, and thinking clearly about how product decisions translate into go-to-market. If your instinct is to manage a backlog rather than own an outcome — or to defer rather than decide — this isn't the right fit.

The product surface that scientists, engineers, and operators use to interact with our autonomous lab — how it's structured, what it exposes, and how it evolves

Feature definition and prioritization across the software layer, informed by close collaboration with internal users and external partners

A clear, opinionated point of view on what the platform should do and what it shouldn't

The AI agent layer that powers our autonomous lab — what tools agents have access to, how they're designed to reason, and where the capability gaps are

Working directly with engineering and ML research to translate scientific and operational requirements into concrete agent tooling and workflow specs

Staying current on the agentic AI landscape; knowing what's newly possible and when it's worth building vs. adopting

Work closely with engineering, science, and ML research to keep the roadmap grounded in both technical reality and user need

Own a genuine, considered design for the overall agentic system — not just feature-level decisions, but how the system fits together

Collaborate with PMs at partner and customer organizations to align on requirements and roadmap priorities

Communicate product direction clearly — to engineers building it and to leadership deciding where to invest

5–7 years in a product management role; ideally with experience at a technical or deep-tech company

Technically credible — you can write code, even if not at production scale; comfort with POC or prototype-level implementation is expected. You read codebases fluently, understand system architecture, and engage with engineers as a peer, not through a translator

Strong user intuition — you know how to identify what's actually needed, not just what's asked for, through close collaboration with scientists and engineers who use what you build

Strong communication and stakeholder management — you can influence without authority across science and engineering teams

Comfortable with ambiguity and first-principles thinking; this is not a role with established processes to follow

Based in New York City