Systems Testing/QA Specialist - Senior

Description

Responsibilities: Provides advice on the testing strategy test plans the selection of testing tools and the identification of resources required for testing Plans and organizes testing efforts for large systems in Graphical User Interface (GUI) and non-Graphical User Interface (GUI) environments including the execution of systems integration tests specialized tests and user acceptance testing (e.g. stress tests) The Quality Assurance Specialist is responsible for the development of test plans test scripts and test cases and executing these against the various components. The tester will work with the testing lead and IT lead of each project as well as the project team members in the analysis design development implementation and ongoing support of the required systems General Skills: Experience in planning organizing and implementing testing efforts at the specified experience level Knowledge of structured methodologies for the development design implementation and maintenance of applications Knowledge and experience in the use of Computer Aided Software Engineering (CASE) tools and data query tools to aid in the development of test cases Knowledge and experience in the use of automated test tools and version control systems on one or more platforms Experience executing functional tests non-functional tests and systems level integration tests Experience supporting user acceptance testing and participating in UAT activities Experience with quality assurance principles practices tools and structured methodologies Experience creating testing strategy documentation test plans test cases and test data for various types and phases of testing including technical and business functional validation Experience in quality assurance and testing including unit testing integration testing load testing performance testing etc. Knowledge and experience in all phases of the Systems Development Life Cycle Excellent analytical problem-solving and decision-making skills; organizational creativity and perseverance skills; verbal and written communication skills; and interpersonal skills A team player with a track record for meeting deadlines Knowledge of one or more automated testing tools Desirable Skills: Knowledge and experience in at least one programming language Experience in the use of information retrieval packages Knowledge and understanding of testing methods in an object-oriented environment Knowledge and understanding of Information Management principles concepts policies and practices. Knowledge and understanding of Accessibility for Ontarians with Disability Act (AODA) and related regulations and standards Experience planning and organizing testing efforts for both large and small systems Experience coding automated test scripts to produce sets of automated test cases Experience testing Commercial Off-the Shelf Applications (COTS)

Skills

Experience and Skill Set Requirements

Project and Digital Experience - 20%

Candidate possesses expert knowledge and proven experience:

• Working in Agile Scrum and DevOps environments.
• Collaborating with multidisciplinary teams including developers designers AI engineers product managers and business SMEs.
• Planning and executing comprehensive testing activities throughout iterative Agile sprints executing continuous validation and ensuring highest accessibility and compliance standards are being met across evolving product increments.
• Using structured workflow and collaboration tools for managing defects throughout their entire lifecycle - from identification and logging through prioritization and triage to resolution verification and closure.
• Working with user stories analyzing business and technical requirements and generating test data requests.
• Applying deep understanding of WCAG 2.1 success criteria (Levels A AA AAA) including principles success criteria and techniques.

Technical Skills - 30%

• Hands-on experience testing web and mobile applications.
• Proficiency in automated testing tools (e.g. Selenium Cypress Playwright).
• Knowledge of AODA compliance testing and tools (e.g. JAWS VoiceOver Axe Accessibility Insights WAVE).
• Experience with CI/CD pipelines and version control systems (e.g. Git Azure DevOps).
• Understanding of image processing and biometric data integrity.

Testing Skills - 35%

• Extensive experience in manual and automated testing across functional non-functional and integration layers.
• Skilled in using data query tools (e.g. SQL Excel) to support test case development.
• Experience supporting and executing User Acceptance Testing (UAT).
• Strong grasp of QA principles tools and structured methodologies.
• Proven ability to create and manage test strategies test plans test cases and reusable test scripts.
• Experience with unit testing load testing performance testing and other specialized testing types.
• Ability to develop modular testing frameworks for scalable and reusable components.

AI Skills and Experience - 15%

• Experience testing AI/ML-enabled applications
• Understanding of AI model behavior including edge cases and bias detection.
• Ability to validate AI-assisted user workflows and ensure biometric integrity.
• Familiarity with AI explainability as well as AI transparency principles.
• Experience with AI testing tools and frameworks (e.g. MLFlow TensorBoard).
• Collaboration with AI engineers to define testable model requirements and performance benchmarks.

Must Haves:

• Experience testing on web/mobile applications
• 10 years of experience as a QA.
• Proficiency in automated testing tools (e.g. Selenium Cypress Playwright).
• Experience testing AI/ML-enabled applications**
• Familiarity with AI explainability as well as AI transparency principles.*
• Ability to validate AI-assisted user workflows and ensure biometric integrity.*
• Experience working with within an Agile environment - DevOps
• applying deep understanding of AODA / WCAG 2.1 success criteria (Levels A AA AAA) including principles success criteria and techniques.

Nice to have:

• Understanding / Experience with AI testing tools and frameworks (e.g. MLFlow TensorBoard).
• Understanding of AI model behavior including edge cases and bias detection.