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.