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Spring Health
San Francisco, CA (Hybrid)
Source: Spring Health careers · View original posting
From Spring Health's posting. “We” and “our” refer to the employer.
Our mission: e liminating every barrier to mental health.
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.
The Senior Director, Product, Platform Intelligence will lead the strategy, roadmap, and business impact of seven teams spanning two pillars of Spring's R&D organization. The Platform pods build the foundational systems that power how members access and move through Spring's services and how internal teams configure and operate the product. The Intelligence pods build the data and AI infrastructure that enables every team at Spring to build, ship, and scale intelligent features quickly and safely.
Please note that this is a hybrid role based in San Francisco
, with an expectation to be in the office 2–3 days per week at our 44 Montgomery Street location. Candidates must be based in the San Francisco metro area or able to relocate independently within 90 days of their start date. Occasional travel will be required for team on-sites.
Platform reliability and performance meet clear service-level standards.
Adoption and self-serve usage of AI/ML platform and data platform capabilities increase measurably across feature teams, with a corresponding reduction in time-to-ship for AI and data-dependent features.
Feature teams measurably use platform and intelligence capabilities not just to ship faster, but to make member experiences smarter and more personalized.
Platform architecture is demonstrably flexible and composable rather than brittle - new capabilities can be built on existing infrastructure without extensive rework, and the platform absorbs changing requirements (new use cases, new models, new regulations) without breaking downstream systems.
Cross-pod roadmap coherence: platform and intelligence investments are demonstrably prioritized against a shared view of business impact, with stakeholders across engineering, clinical, legal, and product aligned on priorities and tradeoffs.
The target base salary range for this position is
$245,000 - $333,000
, 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.
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