Manager, Software Engineering QA

Cricut•South Jordan, UT

4d•Onsite

About The Position

Cricut is seeking a Manager, Software Engineering QA to lead end-to-end quality strategy across Desktop Applications, Mobile (iOS/Android), APIs, and Hardware-connected software. This role involves owning release readiness, quality risk assessment, and go/no-go decisions. The position requires defining clear expectations for feature, API, and system qualification standards, and remaining hands-on when needed by reviewing test strategies, test plans, automation results, and complex defect investigations. The role also includes executing and analyzing automation test suites, and debugging and triaging complex issues across frontend, backend, APIs, and system integrations. A key aspect of this role is the use of AI tools in day-to-day QA activities to improve efficiency and coverage, guiding teams on effective use of AI while maintaining strong engineering and testing judgment, and helping adopt AI-assisted practices to improve QA quality, consistency, and team maturity.

Requirements

12+ years of experience in Software QA / Quality Engineering.
Proven experience as a technical QA lead and people manager.
Strong experience testing Web, Mobile, and API-based applications.
Hands-on expertise in test planning, regression testing, and release qualification.
Experience executing and analyzing automation frameworks.
Working knowledge of AI-assisted QA tools and practices.
Deep understanding of QA methodologies and the SDLC.
Strong communication skills, including presenting to senior and executive stakeholders.
Ability to balance technical leadership with people leadership.
Bachelor’s degree in Engineering or equivalent practical experience.

Nice To Haves

Experience testing software that interacts with hardware.
Experience qualifying consumer electronics products.
Experience leading QA across multiple teams or product areas.
Experience defining quality metrics, dashboards, or large-scale reporting.

Responsibilities

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.
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.
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.
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.
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.