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 companys global Quality Assurance Center of Excellence (QA COE).
This role will define and execute the strategy operating model and roadmap for quality engineering across NetApps 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

Bachelors degree in Computer Science Engineering Information Technology or related field.
Masters degree preferred.