Senior AI Care Operations Manager

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 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. Working within the strategy and priorities established by AI Operations leadership, this person will build effective support workflows, investigate complex issues, and translate conversations into validated insights, AI improvements, and well-supported recommendations for partner teams.

This is a full-time, individual-contributor position with no direct reports. This is a hybrid role based in New York City, with an expectation to be in the office two to three days per week. Our office is located at 60 Madison Avenue. Occasional travel may be required for company or team events.

• →Build, test, launch, and continuously improve AI-powered support workflows that resolve member and provider needs accurately, safely, and efficiently.
• →Translate support policies, processes, and real-world scenarios into clear decision logic and reliable automated experiences.
• →Monitor AI performance and investigate incorrect answers, failed resolutions, routing problems, unnecessary escalations, and information gaps.
• →Own the investigation of suspected AI issues submitted by Care Support and cross-functional partners, from problem reproduction and root-cause analysis through resolution and follow-up.
• →Distinguish between AI, knowledge, process, product, and platform issues; implement fixes within AI Operations and route other issues to the appropriate owner with a clear problem definition.
• →Analyze support conversations to identify recurring member and provider friction, emerging trends, knowledge gaps, and opportunities to reduce avoidable support demand.
• →Validate conversation signals using available evidence and translate meaningful patterns into AI improvements or well-supported recommendations for partner teams.
• →Collaborate with Care Support, Product, Engineering, Enablement and Training, and analytics partners to troubleshoot issues, share evidence, and support solutions within established priorities.
• →Monitor the results of AI Operations changes and provide clear performance insights, risks, and recommendations to AI Operations leadership.
• →Maintain documentation, testing standards, and monitoring practices that enable AI Operations to deliver reliable changes at speed.

• AI-powered support workflows consistently meet agreed targets for resolution quality, routing accuracy, member experience, and operational performance.
• New and updated workflows are launched with effective testing and monitoring, resulting in fewer defects, regressions, and repeat issues.
• High-priority AI-related issues are diagnosed, communicated, and resolved within agreed service expectations, with recurring root causes addressed.
• Meaningful patterns from member and provider conversations are consistently converted into validated AI improvements or actionable recommendations for the appropriate partner teams.
• Improvements owned by AI Operations produce measurable gains in outcomes such as successful resolution, escalation rates, repeat contacts, or member effort.
• AI Operations leadership and cross-functional partners receive clear, evidence-based analysis that supports timely prioritization and decision-making.

• 4-6 years in an operations function — service or care operations, product/program operations, or a comparable role where you owned how work actually got done, not just how it was planned.
• 2+ years at a high-growth or scale-stage company, in a role that was both strategic and hands-on: you set direction and then built the thing yourself.
• Demonstrated hands-on experience building, configuring, testing, or improving automated or AI-powered workflows, decision trees, or similarly complex operational systems.
• Deep understanding of operational workflows and workflow development — how they're designed, where they break, what makes them scale, and how to translate messy policy and edge cases into clear, reliable decision logic.
• Strong analytical capabilities and a data-oriented instinct. You're comfortable getting into the data yourself, and you can move from a pattern in the numbers to a specific, sequenced plan of action.
• A track record of partnering directly with subject-matter experts to learn their workflows in detail, then working alongside them to automate, streamline, or apply AI — earning their trust rather than handing down requirements.
• Rigorous root-cause problem-solving. You can take an ambiguous symptom, reproduce it, isolate whether it's an AI, knowledge, process, product, or platform issue, and drive it to resolution.
• Clear written and verbal communication, with the ability to explain complex issues and influence partners without formal authority.

• Background in Strategy & Operations, Business Operations, or management consulting.
• Experience in Care Support, customer support, or another high-volume support environment.
• Experience building or managing conversational AI or AI-powered support experiences.
• Experience in healthcare, benefits, mental health, or another regulated, high-trust environment.
• Familiarity with prompts, APIs, system integrations, logs, evaluation tools, experimentation, or SQL and basic data querying.

The target base salary range for this position is $97,000 - $124,476 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.