Senior Product Manager, AI & ML Platform

Spring Health is a global mental health company on a mission to eliminate every barrier to mental health. We're building a world where getting support is simple, personal, and built around the person, so care can continue through every job, move, health plan, and life stage.

Our AI-native platform helps us deliver personalized support across self-guided tools, coaching, therapy, medication management, and specialty care. With outcomes independently validated by JAMA Network Open and the Validation Institute, Spring Health reaches more than 170 million people worldwide through leading employers, health plans, and partners.

As an AI-native company, we believe technology should expand the reach, quality, and humanity of care. Every Spring Health team member is expected to use AI tools thoughtfully, apply human judgment to AI outputs, and keep building AI fluency in ways that support their role and our mission.

Reporting to the Senior Director of Product, Customer Value, you will be instrumental in defining and executing the vision for a scalable, secure, and extensible AI/ML foundation. You will build the core machine learning infrastructure and developer platform that powers intelligent features across the company, and enables product teams to rapidly develop, evaluate, deploy, and monitor AI solutions with confidence. 

Please note that this is a hybrid role based in Seattle, with an expectation to be in the office 2–3 days per week at our 255 King St location. Candidates must be based in the Seattle metro area or able to relocate independently within 90 days of their start date. Occasional travel will be required for team on-sites.

• →Shape and drive the AI/ML platform strategy and roadmap. Advance the long-term vision for our core ML infrastructure and AI developer platform, ensuring it enables rapid experimentation, safe deployment, and scalable production use across all product teams.
• →Lead continuous discovery with feature teams. Run an ongoing discovery motion with product, clinical, and engineering teams to deeply understand emerging AI use cases, pain points, and workflow gaps; translate those insights into a clear, prioritized roadmap that balances immediate enablement needs with long-term platform scalability and technical strategy.
• →Align platform investments to business impact. Prioritize infrastructure initiatives based on customer value, scalability, and ROI, ensuring the platform supports enterprise-grade performance, security, and cost efficiency.
• →Define platform solutions in close partnership with Engineering leadership. Collaborate with engineering managers to translate ambiguous AI/ML needs into well-scoped, technically sound platform capabilities, with clear problem statements, success metrics, definition of done, and thoughtful rollout and enablement plans that drive strong adoption among internal developers.

• Establish clear service standards for the AI/ML platform and consistently improve performance, stability, and scalability.
• Build feedback loops with internal teams and measurably improve satisfaction by reducing friction and increasing self-serve capabilities.
• Expand access to high-value data and platform capabilities while reducing the infrastructure burden on feature teams, enabling them to ship impactful AI features more quickly.

• 4+ years of Product Management experience, including ownership of highly technical platforms, infrastructure, or developer-facing products.
• Demonstrated experience partnering deeply with Engineering to ship scalable, reliable systems in production environments.
• Strong understanding of AI/ML systems and workflows (e.g., model lifecycle, evaluation, deployment, observability), with the ability to translate complex technical concepts into clear product direction.
• Track record of driving roadmap clarity in ambiguous, fast-moving spaces and delivering measurable outcomes.
• Experience running continuous discovery with internal users and translating feedback into high-impact platform improvements.
• Ability to define clear success metrics, service standards, and rollout strategies that drive adoption.
• Excellent cross-functional communication skills, with the ability to influence senior technical stakeholders without formal authority.
• Prior machine learning engineering experience is preferred but not required

The target base salary range for this position is $150,000 - 196,880, and is part of a competitive total rewards package including equity and benefits. Individual pay may vary from the target range and is determined by a number of factors including experience, location, internal pay equity, and other relevant business considerations. We review all employee pay and compensation programs annually using Radford Global Compensation Database at minimum to ensure competitive and fair pay.