Software Quality Assurance Analyst (GenAI-Enabled)
Wolters Kluwer•Sherbrooke, QC
•Hybrid
About The Position
We are seeking a highly motivated Software Quality Assurance (SQA) Analyst with a strong Generative AI (GenAI) and automation mindset to join our Quality Engineering team. In this role, you will ensure the delivery of high-quality software by combining traditional QA practices with AI-augmented testing techniques, helping drive the transformation toward Agentic Quality Engineering and intelligent test automation. You will collaborate closely with Product, Development, and DevOps teams to design, execute, and continuously improve testing strategies across the SDLC.
Requirements
- Bachelor’s degree in Computer Science or related field, or equivalent experience
- 3–5 years of experience in software QA in Agile environments
- Strong experience in test case design and execution
- Strong experience in functional and regression testing
- Strong experience in defect lifecycle management
- Hands-on experience with test management and defect tracking tools (e.g., Azure DevOps, Jira, TestRail)
- Solid understanding of SDLC, STLC, and release processes
- Strong analytical, problem-solving, and communication skills
- Familiarity with prompt engineering techniques for test generation and validation
- Understanding of AI agent concepts, workflows, and practical applications within Quality Engineering
- Proficiency in both French and English, spoken and written
- Ability to work in a hybrid environment, with some in-office presence in Sherbrooke
- Practical experience using GenAI tools (e.g., GitHub Copilot, AI assistants) in QA workflows
- Ability to integrate AI into test design and execution
- Ability to integrate AI into automation workflows
- Working knowledge of automation frameworks (e.g., Selenium, Playwright, Cypress)
- Understanding of API testing and data validation (SQL preferred)
- Ability to stay current with evolving AI technologies and apply them in day-to-day testing
Responsibilities
- Analyze requirements and user stories to define comprehensive test scenarios and coverage strategies
- Design, execute, and maintain manual and automated test cases across functional, regression, integration, and system testing
- Perform exploratory, negative, and ad-hoc testing to uncover edge cases and defects
- Document, track, and manage defects through the full lifecycle using QA tools (e.g., Azure DevOps, Jira, TestRail)
- Collaborate with developers to reproduce issues and validate fixes
- Contribute to test planning, estimation, and release validation activities
- Leverage GenAI tools (e.g., GitHub Copilot, AI assistants) to accelerate test case generation, test data creation, and automation script development
- Use AI to identify automation candidates and optimize regression suites
- Validate and evaluate AI-generated outputs and test artifacts for accuracy and completeness
- Contribute to AI-driven testing strategies, including self-healing test automation, risk-based test prioritization, and intelligent defect prediction (where applicable)
- Continuously explore and adopt emerging AI tools to improve QA efficiency and effectiveness
- Use Generative AI tools to accelerate test design, test documentation, defect analysis, and root cause investigation
- Create effective prompts and workflows to generate high-quality test cases, test scripts, and test data
- Contribute to the evaluation and selection of emerging AI tools and technologies for Quality Engineering
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
