Quality Engineering Lead (10+ years) to drive automation-led quality engineering across API-first and AI-assisted validation initiatives

Our financial services client is seeking a Quality Engineering Lead (10+ years) to drive automation-led quality engineering across API-first and AI-assisted validation initiatives

Join a high-impact engineering team shaping the next generation of automated quality practices for member-facing platforms. This senior role blends hands-on software engineering, automation architecture, and team leadership within a modern, API-first, cloud environment. The position offers the opportunity to drive end-to-end quality strategy, integrating AI-assisted testing and automation solutions across distributed systems. This is an engineering-centric role leading scalable, code-driven quality approaches rather than traditional manual testing oversight.

Permanent, Vancouver, Hybrid, Working Hours: PST

Must Haves

• 10+ years in quality engineering, software testing, or related fields with a strong software engineering background
• Hands-on expertise in test automation and scripting using Python, JavaScript, or Java
• Proven experience designing and building automation frameworks integrated within CI/CD pipelines
• Deep experience in API-first testing and reducing reliance on UI-based automation
• Bachelor’s degree in Computer Science, Engineering, or related discipline
• Hands-on experience with Cypress, Playwright, TestNG, or Postman
• Familiarity with AWS or Azure, Docker, and Kubernetes
• Experience with AI-assisted testing, LLM-based automation, or agentic testing approaches
• Exposure to performance, resiliency, and reliability validation in distributed systems

Responsibilities

• Define and implement the quality engineering strategy focused on API-first, automation-driven validation
• Lead and mentor QA/QE engineers to build SDET-level capability and coding proficiency
• Design and build scalable automation frameworks across API, service, and UI layers
• Integrate automation within CI/CD pipelines and ensure outcome-based quality gates
• Collaborate with product, development, and DevOps teams to align on quality objectives and deployment reliability
• Introduce AI-assisted testing techniques to enhance coverage, maintainability, and speed
• Drive continuous validation practices and lead root cause analysis for production issues