Senior Director, Quality Engineering

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.

Contribute to company-wide leadership initiatives including workforce planning, org design, and build-vs-buy decisions on quality tooling and vendors. Define, instrument, and report the quality metrics that leadership and the Board use to assess engineering health. Define and execute the enterprise Quality Engineering strategy, embedding quality across the AI-native SDLC through automation, measurable quality standards, and release governance. Build modern testing frameworks for AI-powered products, LLM applications, and agentic workflows, including automated evaluation, model validation, and continuous quality monitoring.

Drive adoption of AI agents to automate test generation, regression testing, defect analysis, release readiness, and engineering productivity. Establish scalable testing practices across functional, integration, regression, performance, security, accessibility, and end-to-end testing to improve release confidence and reduce production defects. Build reusable testing platforms, automation frameworks, and CI/CD quality tooling that enable engineering teams to own quality and accelerate delivery.

Define validation frameworks that ensure AI systems are reliable, safe, compliant, and trustworthy while partnering with Security, Privacy, Clinical, and AI teams. Ensure testing practices satisfy HIPAA, SOC 2, and applicable clinical and regulatory requirements, validation evidence, auditability, traceability, and PHI-safe test data management. Lead and scale a high-performing, distributed Quality Engineering organization while driving cross-functional alignment and fostering a culture of quality, ownership, and continuous improvement.

Enterprise-wide quality strategy fully integrated into the AI software development lifecycle. Significant improvements in automated test coverage across functional, integration, regression, performance, security, and AI-specific testing. High release confidence with measurable reductions in escaped defects, production incidents, and customer-reported issues. Industry-leading testing frameworks supporting AI-native applications, LLM-powered features, and autonomous agent workflows. AI agents successfully augment Quality Engineering through autonomous test generation, execution, defect analysis, and release intelligence.

Engineering teams adopt quality-by-design principles, resulting in faster release cycles without compromising reliability. Comprehensive trust, safety, and responsible AI validation processes protecting customer experience and regulatory compliance. Quality is a shared responsibility, engineering teams own their quality outcomes, supported by QE platforms and standards rather than dependent on manual QA gates. A high-performing Quality Engineering organization recognized as a strategic partner enabling product innovation rather than slowing delivery.

Proven experience leading and scaling quality engineering organizations (multiple teams across products) in high-growth & fast paced environments, including distributed and globally sourced teams. Deep technical expertise in test automation architecture at scale & modern…