Director of Quality Engineering

Position Summary: Lead the evolution of software quality from traditional QA into a modern Quality Engineering capability that improves release confidence, development velocity, automation, and shared accountability for quality across Product and Engineering.

Key Duties & Responsibilities: Define and execute the enterprise Quality Engineering strategy, operating model, standards, and roadmap. Embed quality throughout discovery, requirements, design, development, and release processes, including strong acceptance criteria and early risk identification. Establish a risk-based quality framework that aligns testing depth and methods to business impact, technical complexity, customer workflows, integrations, and production risk. Build an automation-first testing capability across unit, API, integration, regression, performance, and end-to-end testing, integrated directly into CI/CD pipelines. Apply AI and agentic tooling to accelerate test generation, exploratory testing, regression analysis, defect investigation, test maintenance, and release-readiness assessment. Establish meaningful quality gates, release-confidence criteria, metrics, and feedback loops spanning testing, escaped defects, production incidents, and corrective action. Partner with Software Engineering, Product, Cloud & Platform Engineering, and Information Security to improve testability, resilience, observability, and secure delivery. Develop the internal QE team, retain critical domain knowledge, establish engineering standards and career expectations, and use contractors strategically. Background & Qualifications 10+ years of progressive software engineering, software quality engineering, test automation, or related experience, including significant leadership responsibility. Demonstrated experience transforming manual or downstream QA into an engineering-led, automation-oriented quality capability. Strong technical depth in automated testing architectures, APIs, integration testing, CI/CD, cloud applications, and modern test frameworks. Experience developing risk-based testing strategies for complex, integrated, or high-consequence software systems. Strong understanding of Agile/software-development practices and shared accountability for quality. High proficiency with modern AI tools and frontier models, with demonstrated ability to apply AI safely and productively to testing, automation, analysis, engineering workflows, and team productivity. Experience in healthcare, financial services, regulated technology, or another high-consequence environment preferred. Bachelor’s degree in computer science, engineering, or related discipline, or equivalent relevant experience.