Director, Enterprise Quality Engineering and Agentic Evaluation

Accountabilities:

• Define and lead the enterprise quality engineering strategy, operating model, roadmap, service catalog, standards, and governance framework across the technology organization.
• Own the enterprise quality engineering platform, including test automation and management capabilities, automation assets, integrations, test execution infrastructure, quality reporting, and AI evaluation capabilities.
• Establish risk-based quality models, release-readiness criteria, quality gates, certification standards, and evidence requirements for critical platforms, business processes, integrations, data products, and AI agents.
• Lead a centralized quality engineering service responsible for planning, automating, executing, and governing testing across enterprise products, platforms, transformation programs, and high-risk releases.
• Develop reusable automation frameworks, model-based testing patterns, API and integration testing capabilities, regression suites, and continuous testing practices aligned with business risk and production impact.
• Establish enterprise capabilities for evaluating AI agents, including scenario design, evaluation datasets, regression testing, tool-use validation, policy and permission checks, human escalation criteria, and production quality monitoring.
• Own the enterprise approach to test data, test environments, service virtualization, production validation, and quality analytics to reduce release risk and minimize delivery delays.
• Provide independent quality intelligence, release-risk assessments, and actionable recommendations to engineering, product, program, and executive stakeholders.
• Manage vendor-outsourced quality engineering resources, technology partners, systems integrators, and specialist testing providers to deliver consistent enterprise quality outcomes.
• Build a quality engineering culture centered on automation, objective assurance, reuse, engineering discipline, measurable outcomes, and continuous improvement.

Requirements

• Bachelor’s degree in Computer Science, Engineering, Information Systems, Mathematics, or a related discipline; equivalent relevant experience may be considered.
• 12+ years of experience in quality engineering, software testing, test automation, platform engineering, enterprise technology delivery, or related technology disciplines, including 5+ years leading quality engineering, test automation, enterprise testing, or platform-oriented teams.
• Demonstrated experience building or leading modern quality engineering capabilities beyond manual testing, including automation strategy, risk-based testing, continuous testing, quality gates, and release assurance.
• Strong experience with enterprise test automation and test management platforms, preferably Tricentis Tosca and qTest.
• Proven experience leading testing or quality engineering across multiple products, platforms, business processes, programs, or business units.
• Strong understanding of API, integration, data, workflow, cloud, event-driven, distributed-system, performance, resilience, and production validation testing.
• Practical knowledge of generative AI, large language models, retrieval, AI agents, tool calling, evaluation methodologies, and responsible AI testing practices.
• Strong executive communication and stakeholder management skills, with the ability to influence decisions across technical and business leadership teams.
• Demonstrated organizational leadership, vendor management, financial management, strategic planning, and decision-making capabilities.
• Ability to establish measurable quality standards, translate business risk into engineering requirements, and drive sustainable improvements across complex technology environments.
• Strong analytical mindset and ability to operate effectively in a transformational environment where priorities, technologies, and business needs continue to evolve.
• This position is not eligible for employment-based visa sponsorship, and candidates must already have the required authorization to work in the United States.

Benefits

• Estimated base salary range of $126,600–$194,700 USD annually, with actual compensation varying based on factors such as geographic location, experience, skills, certifications, and organizational needs.
• Potential eligibility for a discretionary annual incentive plan.
• Excellent health, dental, and vision insurance.
• Retirement savings through a 401(k) plan.
• Generous paid time off, including paid parental leave.
• Remote work opportunity.
• Opportunity to shape an enterprise-wide quality engineering strategy and establish foundational practices for agentic AI evaluation.
• High-impact leadership position with broad visibility across technology, product, operations, and business functions.
• Opportunity to work at the intersection of enterprise quality engineering, automation, AI evaluation, and technology transformation.