Senior QA Software Developer (Remote First)
Confirmed on the employer's own hiring board on Oct 17, 2026. First seen by Alion on Aug 6, 2026. Zensurance scores A on the Alion truth index.
We’re looking for a Senior QA Software Developer to join our Core Group.
Reporting to an Engineering Manager, you won’t just be testing - you’ll be designing the future of quality at Zensurance.
The Core Group is the engine room of our platform, consisting of three specialized teams: Docs, Renewals and Pricing, and Core Red. Together, we build and maintain the robust insurance data suite, business rules, and documentation that define our customers' policies. Our stack is primarily MERN (MongoDB, Express, React, Node), and we’ve recently adopted PostgreSQL and BullMQ to push our capabilities even further.
We’re looking for someone who treats quality as a feature, not a hurdle, and who is excited to help us scale a high-traffic insurance platform.
This is a remote-first role within Canada. #LI-Remote
Responsibilities:
Scalable Frameworks: Design, build, and maintain reusable test automation frameworks (integration, E2E, load) that minimize maintenance and maximize reliability. (
Modern Tooling: Leverage AI-assisted development and agentic coding workflows to accelerate test creation and stay ahead of the curve.
Seamless Integration: Partner with developers to bake automated tests directly into our CI/CD pipelines, ensuring quality is never an afterthought.
Full-Spectrum Testing: Balance automated suites with manual exploratory smoke testing and functional testing to ensure every user story meets our "gold standard" before release.
System Resilience: Identify coverage gaps and proactively propose improvements to reduce system fragility and long-term technical debt.
Security & Accessibility: Support our commitment to users by utilizing SAST/DAST tools for security and Axe/Lighthouse to ensure our products are accessible to everyone.
Technical Mentorship: Guide intermediate and junior engineers on testing best practices and the responsible, efficient use of AI coding tools.
Design Influence: Actively participate in design discussions and Agile ceremonies to advocate for testability, maintainability, and clear acceptance criteria.
Culture of Ownership: Promote a shared responsibility for quality across the entire engineering team, documenting strategies and automation patterns for everyone to use.
Data-Driven Improvement: Monitor production incidents and operational data to turn real-world "lessons learned" into future quality improvements.
Automation & Framework Design
Product Quality & Strategy
Leadership & Collaboration
Qualifications:
- 5-8+ years of experience in Test Automation and Quality Assurance.
- Strong experience with modern E2E automation frameworks (Playwright, Cypress, WebDriverIO, Selenium, or similar).
- Experience with JavaScript and/or TypeScript.
- Experience with unit and integration testing frameworks (Jest, Mocha, or similar).
- Experience with API testing and automation.
- Experience with BrowserStack or similar cross-browser testing platforms.
- Experience with manual testing approaches (Functional, Exploratory, UAT).
- Experience working within Agile/Scrum teams.
- Ability to critically review and validate AI-generated outputs for correctness, security, and maintainability.
- Strong communication skills and ability to collaborate cross-functionally.
- Proven ability to take ownership of quality initiatives within a team.
Nice to have:
- Experience with Salesforce or Salesforce-integrated systems.
- Experience testing microservices and micro frontends.
- Experience with monorepos or trunk-based development.
- Experience with SonarCloud / SonarQube.
- Experience with Infrastructure as Code (Terraform, AWS).
- Experience building AI-assisted test generation workflows.
- Experience with accessibility testing tools.
- Familiarity with CI/CD pipelines (e.g., GitHub Actions).
- Experience using AI-assisted development tools (e.g., GitHub Copilot, ChatGPT, or similar) to improve engineering efficiency.
- Understanding of agentic coding concepts, including prompt engineering, AI-generated test case creation, and validating AI-produced code.