Role Overview
The Systems Testing / QA Specialist will provide expert quality assurance and testing leadership for large-scale government systems. This role is responsible for defining testing strategies, developing and executing comprehensive test plans, and ensuring high-quality delivery across web, mobile, and AI-enabled applications. The consultant will work closely with testing leads, IT leads, project teams, and business stakeholders across all phases of the SDLC.
Key Responsibilities
• Define and advise on overall testing strategy, test plans, tools, and resource requirements
• Plan, organize, and execute testing for large systems across GUI and non-GUI environments
• Execute system integration testing, specialized testing, and User Acceptance Testing (UAT), including stress and performance testing
• Develop and maintain testing documentation including test strategies, test plans, test cases, test scripts, and test data
• Collaborate with project teams during analysis, design, development, implementation, and support phases
• Support Agile delivery through continuous testing across iterative sprints
• Manage defects through their full lifecycle using structured defect management tools
• Ensure accessibility, compliance, and quality standards are consistently met
General Skills & Experience
• Extensive experience planning, organizing, and implementing QA/testing initiatives
• Strong knowledge of structured QA methodologies and SDLC best practices
• Experience with automated testing tools and version control systems
• Hands-on experience executing functional, non-functional, and system integration testing
• Proven experience supporting and executing UAT
• Strong analytical, problem-solving, communication, and collaboration skills
• Ability to meet deadlines and work effectively in team-based environments
Skills & Experience Requirements
• Project & Digital Experience (20%)
• Expert experience working in Agile, Scrum, and DevOps environments
• Collaboration with multidisciplinary teams including developers, designers, AI engineers, product managers, and business SMEs
• Planning and executing QA activities throughout iterative Agile sprints
• Managing defects from identification through resolution and closure
• Working with user stories, requirements analysis, and test data requests
• Deep understanding of WCAG 2.1 (Levels A, AA, AAA) principles and techniques
• Technical Skills (30%)
• Hands-on testing of web and mobile applications
• Proficiency with automated testing tools such as Selenium, Cypress, and Playwright
• Experience with AODA compliance testing and accessibility tools (JAWS, VoiceOver, Axe, Accessibility Insights, WAVE)
• Experience with CI/CD pipelines and version control (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
• Experience using data query tools (e.g., SQL, Excel) to support testing
• Strong experience supporting and executing User Acceptance Testing (UAT)
• Proven ability to develop test strategies, test plans, test cases, and reusable test scripts
• Experience with unit, load, performance, and specialized testing
• Ability to design scalable, modular testing frameworks
• AI Skills & 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 biometric integrity
• Familiarity with AI explainability and transparency principles
• Experience with AI testing tools and frameworks (e.g., MLFlow, TensorBoard)
• Collaboration with AI engineers to define testable requirements and performance benchmarks
Must-Have Requirements
• 10+ years of experience as a QA / Testing Specialist
• Experience testing web and mobile applications
• Proficiency with automated testing tools (Selenium, Cypress, Playwright)
• Experience testing AI/ML-enabled applications
• Familiarity with AI explainability and transparency principles
• Ability to validate AI-assisted workflows and biometric integrity
• Strong experience working in Agile / DevOps environments
• Deep understanding of AODA and WCAG 2.1 (Levels A, AA, AAA)
Nice-to-Have
• Experience with AI testing tools and frameworks (MLFlow, TensorBoard)
• Experience identifying AI edge cases and bias
