Senior QA Engineer (Canada)
Summary
Remote (Canada-based) Senior QA Engineer at Zazz: builds and scales automated regression suites with Robot Framework, runs JMeter performance/load tests, embeds quality gates in Azure DevOps CI/CD pipelines, applies AI-assisted testing (GitHub Copilot), and coaches the team on QA best practices.
This is a remote position.
Role Overview
We are seeking a Senior QA Engineer to help reduce manual regression effort, improve release quality, and enable faster, more reliable delivery. The ideal candidate combines deep hands-on test automation expertise with strong performance testing skills, modern CI/CD quality practices, and the ability to coach a team toward QA best practices.
Key Responsibilities
- Design, build, and maintain automated test suites to expand regression coverage and reduce manual effort.
- Develop and execute performance and load tests to validate system reliability and scalability.
- Integrate quality gates into CI/CD pipelines to ensure consistent, reliable releases.
- Apply AI-assisted quality engineering techniques to accelerate test creation and improve coverage.
- Coach and mentor the team on QA best practices, standards, and tooling.
- Collaborate with developers and delivery leads to improve delivery predictability and reduce operational risk.
Required Skills & Experience
- Test automation and regression coverage — designing and scaling automated test frameworks.
- Robot Framework — strong hands-on automation experience.
- JMeter — performance and load testing.
- Azure DevOps — pipelines, boards, and test management.
- CI/CD quality integration — embedding automated quality gates into delivery pipelines.
- AI-assisted quality engineering, including GitHub Copilot, to accelerate testing.
- Demonstrated ability to coach teams on QA best practices.
Nice to Have
- Experience in regulated or public-sector / enterprise delivery environments.
- Familiarity with shift-left testing and quality-engineering culture.
- Exposure to API and integration testing.
Expected Outcomes
Improved delivery predictability, reduced operational risk, and increased engineering efficiency — through stronger automation, reliable performance validation, and embedded quality practices.