QA Engineer, IT Applications & QA

We are hiring a QA Engineer, IT Applications & QA!

Reporting To:

Full-Time/Part
- Time:

Full-time

Salary Range:

$66,685-$106,695

Posting Date:

August 21, 2026

Closing Date:

September 21, 2026

Hours of Work:

8:30 a.m. – 5:00 p.m.

Grade:

Office

Location:

12.4

Toronto

Great location! Steps away from the main public transit station

What we offer:

Highly competitive compensation package which includes, base salary, bonus, benefits, and career advancement opportunities!

* Eligibility for benefits is dependent on the terms of employment

The QA Engineer is accountable forend to endquality assurance of AI enabled mortgage applications and workflows, ensuring that user experiences, APIs, integrations, data flows, business rules, controls, and operational processes work reliably before and after release.

This is ahands onrole embedded in a First National product squad from the start of delivery. The QA Engineer develops and executes risk based manual and automated testing, supports UAT and release readiness, and partners with the AI Quality and Evaluation Lead on the evaluation of probabilistic AI outputs, while retaining clear ownership of functional, integration, regression, and end to end workflow quality.

• Define and maintain arisk basedtest strategy for each product increment, covering functional, integration, end to end, regression, API, data, user interface, accessibility, performance, security control, and operational readiness testing.
• Work with the Product Manager, the Residential Underwriting Business SME, the UX Designer, the AI Engineering Lead, and engineers to turn requirements, policy rules, workflows, exceptions, and acceptance criteria into traceable test scenarios and representative test data.
• Design, execute, and document manual and automated tests across web applications, APIs, services, data pipelines, document processing, permissions, audit logs, notifications, human review queues, calculations, and controlled write back to core systems.
• Build and maintain automated regression suites and CI/CD quality checks using tools such as Playwright, Cypress, Selenium, Postman, Python, .NET test frameworks, SQL, or comparable technologies, and keep tests reliable as products evolve.
• Validate deterministic rules, calculations, data transformations, interface contracts, error handling, recovery,role based access, privacy controls, and release configurations across development, QA, UAT, and production like environments.
• Partner with the AI Quality and Evaluation Lead and AI Engineers to incorporate golden datasets, AI evaluation results, guardrail tests, confidence thresholds, and known failure modes intoend to end product testing, without duplicating enterprise evaluation ownership.
• Collaborate with engineers toimprovesystem testability, observability, logging, and diagnosticcapabilities.
• Coordinate defect triage, severity and priority assessment, root cause investigation, retesting, release evidence, UAT support, parallel runs, and go live readiness, and communicate quality risks clearly to product and control stakeholders.
• Use productiontelemetry,incidents, user feedback, monitoring signals, and escaped defects to strengthen regression coverage, improve testability, and contribute reusable test assets and quality practices across product squads.

• Bachelor’s degree in computer science, engineering, information systems or a related discipline, or equivalent practical experience.
• 5 plus years of progressive quality assurance, software testing, test automation, quality engineering, or related technology experience.
• Strong hands on experience testing web applications, APIs, integrations, data flows, and end to end business workflows, including functional, regression, negative, and production readiness testing.
• Practical experience with test automation and delivery tooling such as Playwright, Cypress, Selenium, Postman, Python, .NET test frameworks, SQL, Git based workflows, CI/CD, defect tracking, and test management tools.
• Experience validating complex business rules, calculations, permissions, auditability, data quality, exception handling, and operational controls in enterprise or regulated environments.
• Working knowledge of AI enabled system testing, including probabilistic outputs, RAG, document intelligence, agents, golden datasets, evaluation metrics, confidence, guardrails, drift, and human in the loop controls is strongly preferred.
• Experience supporting UAT, parallel runs, release…