Role Summary -
We’re looking for a Senior QA Manager to lead and transform our Engineering's QA function as our engineering organization scales. This role is about taking an existing QA team and evolving it into a modern, automation-first, AI-enabled quality organization that empowers engineers to move fast with confidence. You’ll be responsible for people, process, and technology - building a high-performing team, modernizing our testing strategy, and embedding quality deeply into how we build and ship software.
What You Will Do -
Lead & Grow the QA Team
- Manage, mentor, and grow a team of QA engineers across experience levels
- Establish clear roles, expectations, and career paths within QA
- Foster a culture of ownership, collaboration, and continuous improvement
- Partner with engineering leadership to plan team growth and resourcing
Own & transform QA Practices
- Assess current QA processes and lead a transition to an automation-first, AI-augmented testing strategy
- Drive adoption of modern testing frameworks, tooling, and best practices
- Reduce reliance on manual testing through intelligent automation and AI-assisted workflows
- Define what “quality at scale” means for the organization and implement it pragmatically
Embed Quality into Engineering
- Shift QA left by partnering closely with engineering and product leaders
- Ensure quality is built into design, development, and deployment - not treated as a final gate
- Establish scalable standards for test coverage, reliability, and release confidence
- Champion shared ownership of quality across teams
Leverage AI & Automation
- Introduce and operationalize AI-powered QA tooling for test generation, maintenance, prioritization, and analysis
- Use data and AI insights to identify risk areas, flaky tests, and systemic quality issues
- Evaluate, select, and roll out new QA and AI tools with a focus on real-world impact
- Balance innovation with stability - knowing when AI helps and when it doesn’t
Drive Continuous Improvement
- Improve CI/CD quality signals and release confidence
- Track and communicate quality metrics that matter (not vanity metrics)
- Continuously refine processes as teams, systems, and products evolve
What You Will Bring -
- QA Automation & Development:
- Minimum of 5 years in QA automation, SDET, or software engineering with a primary focus on testing.
- Proven hands-on ability to build and scale automated test frameworks within growing engineering organizations.
- Strong proficiency with modern test frameworks (e.g., Playwright, Cypress, Selenium, Jest, PyTest) and a deep understanding of the full testing pyramid (unit, integration, API, smoke, sanity, regression, E2E).
- Experience testing APIs, distributed systems, and complex data-driven applications.
- AI/ML in QA:
- Experience implementing AI-assisted QA workflows or tools in production environments.
- Experience using or integrating AI-powered testing tools (e.g., AI-generated tests, self-healing frameworks, intelligent monitoring).
- Familiarity and comfort working in development environments where AI is integral (code generation, test generation, analysis).
- Hands-on experience with agentic AI workflows and building reliable test coverage around autonomous, multi-step processes.
- Experience evaluating and selecting modern QA and AI tooling.
- Systems, Data, and Infrastructure:
- Solid understanding of CI/CD pipelines, test orchestration, and deployment workflows.
- Exposure to performance, load, or reliability testing, especially when enhanced by automation or AI.
- Familiarity with major cloud infrastructure platforms (AWS, GCP, or Azure).
- Solid understanding of database fundamentals, including SQL, data flows, and designing data-driven test scenarios for data layer verification.
- Leadership & Growth
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- Experience scaling QA practices from early-stage to growth-stage teams.
- Strong communication skills and a pragmatic, systems-oriented mindset.