Manager, Software Engineering QA

Quality & Technical Leadership 

• Lead end‑to‑end quality strategy across Desktop Applications, Mobile (iOS/Android), APIs, and Hardware‑connected software. 
• Own release readiness, quality risk assessment, and go/no‑go decisions. 
• Define clear expectations for feature, API, and system qualification standards. 
• Remain hands‑on when needed by reviewing test strategies, test plans, automation results, and complex defect investigations. 
• Execute and analyze automation test suites. 
• Debug and triage complex issues across frontend, backend, APIs, and system integrations. 

AI‑Enabled QA Leadership 

• Use AI tools in day‑to‑day QA activities to improve efficiency and coverage, including:  
• Change log and release notes validation 
• Fix analysis to verify defect resolutions and prevent regressions 
• Identifying impacted areas across frontend, backend, APIs, and hardware‑integrated workflows 
• Test case generation and optimization 
• Risk analysis and test prioritization 
• Log analysis and defect investigation 
• Guide teams on effective use of AI while maintaining strong engineering and testing judgment. 
• Help adopt AI‑assisted practices to improve QA quality, consistency, and team maturity. 

People & Team Leadership 

• Manage and mentor QA engineers and QA leads, providing technical guidance, performance feedback, and career growth support. 
• Coach engineers on test strategy, risk‑based testing, automation thinking, and quality ownership. 
• Balance delivery execution with long‑term team development and scalability. 
• Build strong team capability through coaching, standards, and best practices. 
• Help scale QA by improving execution consistency, predictability, and maturity. 

Cross‑Functional & Stakeholder Leadership 

• Partner closely with Product Management and Engineering to ensure requirements are testable, measurable, and aligned to customer impact. 
• Represent QA in cross‑functional forums, release discussions, and leadership reviews. 
• Communicate quality status, risks, dependencies, and trade‑offs clearly to stakeholders and executive leadership. 
• Present data‑driven quality metrics and insights to support decision‑making. 

Process & Continuous Improvement 

• Continuously improve QA processes, workflows, and best practices across teams. 
• Contribute to defining and evolving quality metrics, dashboards, and operational reporting. 
• Drive improvements in test efficiency, automation effectiveness, reliability, and release predictability.