Senior Director, Quality Engineering

Our mission is eliminating every barrier to mental health. Spring Health is a global mental health company 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 delivers 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. We reach more than 170 million people worldwide through leading employers, health plans, and partners.

About the role

As a senior engineering leader, you will shape and execute the quality strategy for everything we ship. You will define what "high quality" means for an AI-native healthcare company by building testing frameworks, agentic quality systems, and evaluation infrastructure that enable faster releases with greater confidence and earn clinical and enterprise trust in AI-driven features.

Reporting to the SVP of Engineering, you will lead the Quality Engineering organization, driving org-wide testing strategy, intelligent automation, and AI-powered quality practices across the software development lifecycle. You will partner with Engineering, Product, Design, Infrastructure, Security, and Data Science leaders to embed quality throughout development—not just validate software before release. This role is hybrid based in San Francisco, with an expectation to be in the office 2–3 days per week. 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.

Responsibilities

• 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, including 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.

What success looks like

• 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.

Requirements

• Proven experience leading and scaling quality engineering organizations (multiple teams across products) in high-growth and fast-paced environments, including distributed and globally sourced teams.
• Deep technical expertise in test automation architecture at scale and modern frameworks (e.g., Playwright, Cypress, pytest, Jest), CI/CD integration, contract and API testing, performance and resilience testing.
• Hands-on experience building evaluation and testing systems for AI/ML or LLM-powered products: eval harnesses, golden datasets, LLM-as-judge, regression testing across model and prompt changes, red-teaming, and guardrail validation.
• Demonstrated experience deploying AI agents or AI-assisted tooling into the SDLC, test generation, triage, maintenance, or code review with measurable productivity gains.
• Strong track record of shift-left transformation: moving organizations from manual QA gatekeeping to engineer-owned quality with platform support.
• Experience with quality in regulated or high-consequence domains (healthcare, fintech, or similar), including HIPAA/SOC 2, PHI-safe test data, and audit and traceability requirements.
• Strategic mindset with the ability to balance long-term vision and hands-on execution; credible in deep technical design reviews.
• Strong cross-functional leadership and communication skills, with the ability to influence at executive levels and make quality trade-offs legible to non-engineering stakeholders.
• Demonstrated ability to drive measurable outcomes (e.g., escaped defect rate, change failure rate, test cycle time, automation coverage, eval pass rates, cost per release).

Pay

The target base salary range for this position is $230,000 - $250,000, 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 factors including experience, location, and internal pay equity.

Benefits

• Health, Dental, and Vision benefits starting on your first day, including access to One Medical accounts for you and your dependents.
• HSA and FSA plans available, with Spring contributing up to $1K for HSAs depending on plan type.
• Employer-sponsored 401(k) match of up to 2% for retirement planning.
• Yearly allotment of no-cost visits to the Spring Health network of therapists, coaches, and medication management providers for you and your dependents.
• Competitive paid time off policies including vacation, sick leave, and company holidays.
• Parental leave of 18 weeks for birthing parents and 16 weeks for non-birthing parents, available at 6 months tenure.
• Access to Noom, a psychology-based weight management program tailored to your unique needs and goals.
• Fertility care support through Carrot, plus $4,000 reimbursement for related expenses.
• Access to Wellhub, connecting employees to fitness, mindfulness, nutrition, and sleep resources in one subscription.
• Access to BrightHorizons for sponsored child care, back-up care, and elder care.
• Up to $1,000 Professional Development Reimbursement per year.
• $200 per year donation matching to support your favorite causes.