Director, SW QA Engineering

Job Summary

NetApp is seeking a visionary and transformational leader to serve as Director, Software QA Engineering, responsible for leading the company's global Quality Assurance Center of Excellence (QA COE).
This role will define and execute the strategy, operating model, and roadmap for quality engineering across NetApp's enterprise application ecosystem. The Director will lead a globally distributed organization responsible for quality governance, automation, AI-driven testing, end-to-end business process validation, performance testing, test platform engineering, and release quality management.

The successful candidate will inherit a maturing QA organization and lead its continued evolution toward an AI-first Quality Engineering model focused on:
•    End-to-end business process testing
•    Intelligent test automation
•    AI-assisted quality engineering
•    Predictive defect prevention
•    Enterprise-wide quality governance
•    Release confidence and business continuity

This leader will partner across enterprise architecture, software engineering, product teams, business process owners, and executive leadership to ensure quality is embedded throughout the software delivery lifecycle. 

Job Requirements

Enterprise QA Leadership
•    Define and execute the multi-year Quality Engineering strategy and roadmap.
•    Establish quality as a measurable business capability and competitive advantage.
•    Drive transformation from traditional testing to AI-enabled quality engineering.
•    Build a scalable operating model supporting enterprise growth and digital transformation.
End-to-End Business Process Quality
•    Establish ownership and accountability for end-to-end business process validation across integrated enterprise systems.
•    Drive cross-functional quality initiatives spanning Commerce, ERP, Supply Chain, Service Management, Customer Support, and Professional Services.
•    Ensure release readiness and business continuity through comprehensive testing strategies.
AI and Automation Strategy
•    Lead the deployment and adoption of AI-enabled testing solutions.
•    Drive intelligent automation across regression, integration, and release testing.
•    Identify opportunities to leverage generative AI, predictive analytics, and machine learning to improve software quality and engineering productivity.
•    Champion innovation and experimentation in quality engineering practices.
Operational Excellence
•    Establish quality governance frameworks, KPIs, and reporting mechanisms.
•    Improve release confidence through automation, defect prevention, and early quality validation.
•    Drive continuous improvements in testing efficiency, cycle time, quality outcomes, and user experience.
•    Define and monitor quality metrics including test coverage, defect leakage, automation effectiveness, and release readiness.

Education

•    Bachelor's degree in Computer Science, Engineering, Information Technology, or related field.
•    Master's degree preferred.