Director of Quality Engineering

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.