Senior AI Product Manager, Healthcare Agents

Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including frontier model training, enterprise adoption, defense applications, and autonomous vehicles. Our mission is to develop reliable AI systems for the world’s most important decisions. We’re looking for an AI Product Manager to own the Healthcare vertical within our Agents Data & Reinforcement Learning Environments team. In this role, you’ll own both the development of RL environments (the realistic, high-fidelity simulations of healthcare software and workflows that labs use to train and evaluate agents) and the “data as a product” strategy that powers them. You’ll understand where AI is being used in the Healthcare industry, decide what healthcare tasks are worth modeling, how to source and structure the underlying data, and how to turn deep domain knowledge into a defensible product. The ideal candidate has lived inside the Healthcare industry, and is able to pair that domain understanding with a sense for AI research and current agent capabilities in Healthcare workflows. You’ll translate that expertise into environments and datasets that teach AI agents to perform real healthcare work, and you’ll be the domain expert Scale’s most important customers and their leading researchers turn to. A strong entrepreneurial & go-to-market mindset will be necessary. What You’ll Do Own the Healthcare AI roadmap & data strategy: Set product direction for the Healthcare agents training stack and the data strategy behind it. Establish a vision for where AI is continuing to transform the Healthcare industry, driving execution across engineering, operations, and go-to-market teams. Build partnerships with research teams at frontier labs: Work directly with researchers at leading AI labs to understand where their Healthcare agentic capabilities fall short and shape new product lines and competitive strategy for the vertical. Connect with AI startups and industry leaders to launch joint benchmarks and build Scale’s brand in Healthcare. Design and scale Healthcare-specific environments: Scope and build simulations of real Healthcare workflows and environments that let labs train and evaluate agents against real world scenarios. Partner with ML and Operations to translate the judgement, edge cases, and workflows you know from the industry into high quality training products. Collaborate cross-functionally — influence business priorities and dive into the weeds of research, operations, and customer interactions to deliver mission-critical outcomes. Ideally, You’d Have 2–4 years of direct experience in the Healthcare industry in one or more of: healthcare research, clinicians & clinical staff using EHRs daily, revenue cycle management, or a healthtech product role, with real depth in how the work gets done. AI-Forward Thinking : Quick to adopt AI solutions to streamline your day-to-day workflows and an ability to understand and articulate how it’s transforming your industry. A builder’s mindset: excited by ambiguity and motivated to create new products from the ground up. Product or customer-facing experience: A track record of owning outcomes, shaping roadmaps, or working closely with technical stakeholders (formal PM experience is a plus but not required if domain depth is strong). ML Intuition & Technical Fluency: Enough intuition around how model training and evaluation works and what a Reinforcement Learning environment looks like. A software background is a plus. Bias for action: Comfort wearing multiple hats and operating in fast-moving environments. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is: $205,600 — $257,000 USD PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. 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