Director of Quality Engineering

Essential Job Duties

Enterprise Quality Leadership: Develop, implement, and lead the overall quality strategy and QA operating model across the organization.
Standardize Testing Processes: Define and enforce consistent testing approaches including test planning, test cases, regression strategy, and release readiness criteria.
Tooling Ownership: Select, implement, and manage enterprise testing tools for test management, automation, performance, accessibility, and security validation.
Automation Strategy: Drive increased automated test coverage across UI, API, mobile, and services, reducing reliance on manual regression testing.
Compliance, Accessibility & VPAT Reporting:
Lead accessibility testing programs aligned to WCAG 2.1+
Oversee creation and maintenance of Voluntary Product Accessibility Templates (VPATs) and Accessibility Conformance Reports
Partner with Product, Legal, and Compliance to respond to customer accessibility requirements and audits
Security & Compliance Testing Support: Coordinate with Security teams on SAST/DAST, vulnerability validation, and remediation tracking.
Customer UAT Support:
Define and support customer UAT strategies and environments
Provide test plans, data guidance, and defect triage support during customer acceptance testing cycles
Ensure feedback from UAT informs release decisions and product quality improvements
Quality Metrics & Reporting: Establish KPIs to measure product quality, defect escape rate, automation coverage, UAT outcomes, and release readiness; communicate results to leadership.
Shift-Left Quality Practices: Embed quality earlier in the development lifecycle through collaboration on requirements, acceptance criteria, and CI/CD integration.
Incident & Defect Management: Oversee defect triage for high-priority production and pre-production issues and ensure timely resolution and root-cause prevention.
Cross-Functional Collaboration: Work closely with Product Management, Engineering, DevOps, Security, and Compliance to ensure alignment of quality practices across releases.
Organizational Leadership: Build, mentor, and lead a high-performing team of QA engineers, SDETs, automation engineers, and accessibility/compliance testers.
Continuous Improvement: Identify quality gaps and drive process improvements that improve product reliability, reduce rework, and increase delivery confidence.
Release Governance: Participate in release readiness reviews and serve as a key stakeholder in go/no-go decisions.
Coding agent advocacy: Help onboard team members to AI development tools. Share techniques, prompt patterns, and review practices that make AI-augmented development effective and safe in a regulated environment.

Other Job Duties

Other duties as assigned by supervisor or HHAeXchange leader.

Travel Requirements

• Travel up to 10%, including overnight travel

Required Education, Experience, Certifications and Skills

Bachelor’s degree in Computer Science, Engineering, or a related field required.
10+ years of experience in software engineering within a software product company, with a focus on developing scalable, high-performance systems.
4+ years leading QA organizations or enterprise quality programs.
Proven experience designing and implementing standardized QA processes and test automation strategies in SaaS environments.
Hands-on experience implementing automated testing frameworks integrated into CI/CD pipelines.
Experience with accessibility testing and standards such as WCAG 2.1+ and authoring VPATs/ACRs.
Experience supporting security testing practices such as vulnerability scanning, SAST/DAST, and penetration test remediation validation.
Experience supporting or running customer UAT processes.
Strong understanding of quality metrics (defect rates, coverage, MTTR, escape rate, etc.) and how to operationalize them.
Background working in cloud-based architectures and microservices environments.
Demonstrated success collaborating across engineering, product, and security teams in a fast-paced environment.
Strong leadership skills with experience managing and developing QA and automation teams.
Excellent verbal and written communication skills, including the ability to communicate complex topics to technical and non-technical partners.
AI/ML fundamentals: Familiarity with LLM APIs, prompt engineering, and how generative AI can be applied in a product context. Direct project experience preferred.