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Spring Health is a global mental health platform on a mission to eliminate barriers to mental health care. The company operates an AI-native platform delivering personalized support through self-guided tools, coaching, therapy, medication management, and specialty care, reaching over 170 million people worldwide through employers, health plans, and partners.
Reporting to the Director of AI Operations, the Senior AI Care Operations Manager will own the hands-on development, performance, and continuous improvement of AI-powered member and provider support experiences. This is a full-time individual contributor role (no direct reports) based in New York City on a hybrid schedule (2-3 days per week in office at 60 Madison Avenue).
Key responsibilities include:
- Building, testing, launching, and continuously improving AI-powered support workflows that resolve member and provider needs accurately, safely, and efficiently
- Translating support policies, processes, and real-world scenarios into clear decision logic and reliable automated experiences
- Monitoring AI performance and investigating incorrect answers, failed resolutions, routing problems, and information gaps
- Owning investigation of suspected AI issues from problem reproduction through root-cause analysis and resolution
- Distinguishing between AI, knowledge, process, product, and platform issues; implementing fixes or routing appropriately
- Analyzing support conversations to identify recurring friction, emerging trends, knowledge gaps, and opportunities to reduce avoidable support demand
- Validating conversation signals and translating meaningful patterns into AI improvements or recommendations for partner teams
- Collaborating with Care Support, Product, Engineering, Enablement, and analytics partners to troubleshoot and support solutions
- Monitoring results of AI Operations changes and providing performance insights and recommendations to leadership
- Maintaining documentation, testing standards, and monitoring practices enabling reliable changes at speed
Success metrics include AI workflows consistently meeting targets for resolution quality and member experience, effective testing and monitoring of new workflows, timely diagnosis and resolution of high-priority issues, conversion of conversation patterns into validated improvements, measurable gains in outcomes like successful resolution and escalation rates, and providing clear evidence-based analysis to support decision-making.
Required experience: 4-6 years in operations (service, care, or product/program operations) where you owned how work got done; 2+ years at high-growth or scale-stage companies in strategic and hands-on roles; demonstrated hands-on experience building, configuring, testing, or improving automated or AI-powered workflows and decision trees; deep understanding of operational workflows, their design, failure modes, and scaling requirements.
