Job Description

Accountabilities:

• Lead day-to-day QA technical activities within Agile/Scrum teams, including planning, standups, reviews, retrospectives, estimation, and technical discussions.
• Review business requirements and user stories, break work into actionable tasks, evaluate technical options, and collaborate with Product Management on solutions and priorities.
• Own small to mid-sized QA engineering projects and product areas, defining and overseeing automation strategy and quality delivery.
• Design, develop, and maintain reusable, scalable test automation frameworks and components using modern engineering practices.
• Establish and promote standards, patterns, architecture principles, documentation, and best practices for test automation.
• Lead the adoption of Generative AI and AI-native QA practices, including AI-assisted test generation, intelligent defect triage, predictive quality analysis, and intelligent test maintenance.
• Evaluate and implement AI tools, agent-based QA solutions, and AI-enabled development workflows that can improve test coverage, efficiency, and precision.
• Use tools such as GitHub Copilot, ChatGPT, Claude, or equivalent platforms to accelerate test case creation, test data generation, documentation, and quality workflows.
• Architect and implement UI visual regression testing capabilities using technologies such as Applitools, Percy, Playwright, or comparable solutions.
• Define visual testing baselines, comparison strategies, tolerance thresholds, and quality gates across browsers and device viewports.
• Partner with frontend engineering and design teams to align visual testing with design system standards and accessibility requirements.
• Lead DORA metrics measurement and improvement initiatives, establishing baselines, targets, dashboards, and actionable insights for engineering teams.
• Identify quality and process bottlenecks affecting deployment frequency, lead time, change failure rate, and mean time to restore, and drive initiatives to improve these outcomes.
• Collaborate with DevOps, SRE, platform engineering, development, product, and other teams to align QA practices with reliability and delivery goals.
• Review team members' work, conduct code and automation reviews, and identify architectural or testability improvements.
• Troubleshoot and reproduce customer-reported issues and contribute to timely resolution.
• Mentor QA and engineering professionals, promote knowledge sharing, and help elevate the broader quality engineering practice.
• Evaluate emerging technologies, tools, and testing practices and assess their suitability for the QA technology ecosystem.

Requirements

• Bachelor's degree in Computer Science, Software Engineering, Quality Assurance, or a related field, or equivalent professional experience.
• 6+ years of experience in software development, SDET, Quality Engineering, or test automation, with a strong focus on automation.
• Strong proficiency in TypeScript for test automation, tooling, and framework development.
• Solid understanding of unit, integration, load, functional, and related software testing approaches.
• Experience across the full software development lifecycle, including design, development, testing, deployment, upgrades, and production support.
• Hands-on experience with REST API testing and automation.
• Strong knowledge of BDD and TDD methodologies.
• Familiarity with SQL databases and queries for test data validation.
• Experience with exploratory testing and the ability to adapt testing techniques to different contexts.
• Experience working with CI/CD tools and integrating automated quality practices into delivery pipelines.
• Demonstrated hands-on experience with Generative AI tools such as GitHub Copilot, ChatGPT, Claude, or equivalent platforms applied to software engineering or QA workflows.
• Experience implementing UI visual regression and comparison testing frameworks such as Applitools, Percy, Playwright, or similar tools within CI/CD pipelines.
• Proven experience contributing to or leading DORA metrics measurement and improvement initiatives across engineering teams.
• Experience testing technically complex systems, including microservices and distributed architectures with fail-safe or high-reliability requirements.
• Experience applying shift-left testing during development and shift-right testing in production environments.
• Strong problem-solving, critical-thinking, analytical, and attention-to-detail skills.
• Excellent communication and influencing abilities when working with developers, Product Managers, architects, and other stakeholders.
• Knowledge of performance, scalability, security, reliability, and other non-functional testing concepts.
• Experience building or evaluating AI-powered test generation and intelligent test maintenance solutions is a strong advantage.
• Familiarity with prompt engineering for QA automation, test case design, and AI-assisted testing is desirable.
• Experience with agentic IDE development and testing practices is a plus.
• Hands-on experience with security and performance testing is desirable.
• Experience establishing or owning engineering metrics programs beyond DORA is an advantage.
• Previous experience with fitness, wellness, or multi-tenant SaaS products is a plus.

Benefits

• Annual compensation of CA$95,000–CA$100,000, with final compensation determined by experience, qualifications, skills, location, and market factors.
• Potential eligibility for additional compensation such as bonuses, commissions, equity, or other incentive programs, where applicable.
• Remote work opportunity in Canada.
• Open PTO policy providing flexibility in how and when time off is taken.
• Quarterly company-wide Days of Disconnect
• Parental and pawternity leave.
• Quarterly fitness and wellness reimbursement.
• Medical, dental, and vision coverage.
• Employee Assistance Program (EAP).
• Premium Calm App subscription for employees and up to four dependents over age 16.
• Continuous learning, professional development, and training opportunities.
• Inclusive culture focused on collaboration, growth, belonging, and employee well-being.
• Opportunity to work with AI-native engineering practices and influence the evolution of modern Quality Engineering.
• Technical leadership and mentoring opportunities without requiring direct people management.