Staff Product Manager, Agentic Systems

Role Summary

Staff Product Manager for Agentic Systems responsible for defining the technical and scientific capabilities for the next suite of autonomous science capabilities. You will sit at the intersection of a massive proprietary data generation engine and cutting-edge AI models, building the "nervous system" that allows agents to reason, plan, and execute experiments in automated labs. This role focuses on frontier technology, prioritizing autonomous science capabilities with the most impact on the drug discovery pipeline, while balancing durable orchestration infrastructure with cycles of experimentation. This is an office-based, hybrid role with locations in Salt Lake City, Utah or New York City, New York; in-office presence is expected at least 50% of the time.

Responsibilities

• Define the Architecture for Autonomy: Partner with engineering leadership to scope and build the systems that connect in silico models (the "brain") with physical automated labs (the "body"), enabling closed-loop, autonomous discovery.
• Drive Hypothesis-Driven Product Development: Lead cycles of experimentation to test different agentic frameworks. Embrace ambiguity, helping the team decide when to build durable shared services and when to build rapid, throw-away prototypes to learn what works.
• Operate as a Translator: Bridge the gap between "wet lab" realities and "dry lab" possibilities. Translate the needs of drug discovery programs into technical requirements for agent reasoning, ensuring systems optimize for information gain rather than just volume.
• Evangelize the "Human-in-the-loop" Evolution: Work with scientific stakeholders to define interfaces where humans review, validate, and shape agent reasoning, ensuring scientists evolve from "operators" to "architects" of discovery.

Qualifications

• Navigating Ambiguity in Technical Products: 5+ years of product management experience, with a focus on platform, infrastructure, or AI/ML products where the technical solution was not immediately obvious.
• Experimentation-First Mindset: Proven track record of managing products through rapid prototyping cycles; understanding when to build durable shared services versus rapid prototypes to learn what works.
• Technical Fluency in Modern AI: Fluent in LLMs, agentic workflows, APIs, and modern data infrastructure; able to engage in discussions about orchestration architectures.
• Systems Thinking: Ability to visualize complex ecosystems and understand how changes propagate through downstream decision-making.
• Communication & Influence: Strong written and oral skills to align diverse stakeholders (PhDs in Biology, Robotics Engineers, AI Researchers) around a unified technical vision.

Skills

• Technical Fluency in Modern AI
• Agentic Workflows and API Literacy
• Systems Thinking
• Cross-functional Communication