QA Manager

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Requirements:

• Proven ability to lead QA teams, instilling a sense of ownership and continuous improvement.
• Deep hands-on technical knowledge of QA methodologies, testing frameworks, and automation tools.
• Strong background in developing and implementing metrics to measure QA effectiveness, product quality, and process efficiency.
• Hands-on success using AI tools for increased efficiency and quality, and experience driving adoption of those tools within a QA team.
• Demonstrated success in identifying process inefficiencies and implementing improvements, including the adoption of AI and automation technologies.
• Proficiency with QA tools, automation frameworks, and modern development practices.
• Understanding of CI/CD pipelines and how QA integrates with them.
• Leadership in building a culture of quality that impacts the organization as a whole, not just QA.
• Ability to work closely with engineering, product, and customer-facing teams to align QA efforts with broader business goals and customer needs.
• Experience leading organizational change, particularly in transitioning QA teams to more flexible and efficient structures.
• Strong written and verbal communication skills to articulate QA strategies, metrics, and process changes to both technical and non-technical stakeholders.
• Focused on improving product reliability and performance to enhance customer satisfaction, with an understanding of customer pain points and feedback loops.
• Demonstrates curiosity and willingness to adopt new technologies and methodologies, continuously evolving the QA function to meet emerging challenges and industry standards.

Responsibilities:

• Use first-hand experience to introduce better talent, tooling, and process to drive a meaningful reduction in escaped defects.
• Develop and deploy comprehensive metrics to assess the effectiveness of QA efforts and the overall quality of our products.
• Improve breadth and depth of test coverage through hands-on technical experience across all layers of the testing pyramid.
• Integrate AI-driven automation tools to increase testing efficiency and accuracy.
• Evaluate current QA personnel, foster professional growth, and increase talent density within the team.
• Assess QA resourcing and make necessary changes to reduce specialization silos, increase efficiency, and drive better quality outcomes.
• Hit the ground running by creating and executing on a 90 day plan with ambitious outcomes and clear metrics for success.