We are looking for a highly experienced and hands-on Principal Quality Engineer to define and drive quality engineering standards across a growing engineering organization. In this strategic and technical leadership role, you will take ownership of the company-wide quality vision, evolving existing testing practices, infrastructure, and AI-powered tools. You will work closely with engineering leaders and QA professionals to establish consistent quality standards while empowering teams to take greater ownership of software quality. A key focus will be advancing AI-native testing capabilities, strengthening CI/CD pipelines, and improving automated testing across the entire technology stack. You will also mentor QA engineers across multiple teams, promote continuous improvement, and introduce innovative approaches to software testing. This is an opportunity to shape the future of engineering quality in a fully remote, collaborative, and technology-driven environment with strong leadership support.
Quality Strategy and Vision: Own and continuously evolve the company-wide quality engineering roadmap, establishing clear standards, priorities, and accountability frameworks for engineers, Engineering Managers, and Product Managers throughout the software development lifecycle.
Testing Strategy: Define and improve testing approaches across the entire technology stack, including unit, component, contract, API, end-to-end, mobile, and non-functional testing such as performance, load, and accessibility testing.
AI-Native Quality Engineering: Drive the adoption and evolution of AI-powered quality tools, including AI agents and skills that support automated test generation, code reviews, and on-demand quality guidance. Explore emerging AI capabilities and identify opportunities to integrate them into engineering workflows.
CI/CD and Test Infrastructure: Own and improve automated testing infrastructure, quality gates, required checks, end-to-end testing pipelines, visual regression testing, performance budgets, and mobile automation strategies across emulators and real-device cloud environments.
Pipeline Optimization: Determine which quality checks should block deployments and which can run asynchronously, ensuring reliable testing processes without compromising development speed or delivery efficiency.
Production Quality and Monitoring: Connect production monitoring with incident response processes and develop meaningful quality dashboards that engineering teams actively use to track performance and identify issues.
Technical Leadership and Mentorship: Provide technical direction and mentorship to QA engineers across multiple engineering squads, helping them strengthen their testing practices, share knowledge, and adopt consistent standards.
Cross-Functional Collaboration: Partner with Engineering Managers, Product Managers, and engineering teams to embed quality ownership into everyday development practices and ensure quality improvements are treated as planned engineering work.
Continuous Research and Innovation: Evaluate emerging testing methodologies, technologies, and AI capabilities, experimenting with new approaches and determining which innovations should be adopted across the organization.
Technical Enablement: Lead knowledge-sharing initiatives, coaching sessions, and practical training to improve testing maturity and empower engineers to take greater responsibility for software quality.
Quality Performance: Establish measurable improvements in test reliability, pipeline efficiency, automation coverage, and overall engineering quality.
Future Team Leadership: As the QA organization grows, potentially take on direct people management responsibilities, including recruitment, coaching, professional development, and performance management.