QA Team Lead

Test strategy and delivery

• Define the test strategy, scope, entry and exit criteria, and release readiness measures for each engagement, based on business requirements and risk.
• Plan testing across environments hosted in Azure or on premises, including environment readiness, configuration, and test data.
• Estimate and plan QA effort, assign work to Practitioners, and track progress against the project plan.
• Oversee the design of functional and regression test suites, and decide which scenarios to automate and which to keep manual.
• Plan and coordinate UAT with business users: prepare scripts and test data, run sessions, collect feedback, track defects to closure, and report readiness for acceptance.
• Lead defect triage with developers, business analysts, and project managers.
• Maintain traceability from requirements and user stories to test cases and defects.
• Report status, risks, and quality metrics to stakeholders and to the engagement lead.

Test automation

• Build and maintain an automation framework for web UI, API, and integration regression testing, using a modern framework such as Playwright, Selenium, or Cypress, in a language that suits the project such as C#. Set coding standards and reusable components.
• Design API and integration tests for .NET services and the systems they connect to.
• Integrate automated regression into continuous integration and delivery (CI/CD) pipelines, using tools such as Azure Pipelines, GitHub Actions, or similar. Where it helps, run suites in parallel on a cloud browser service.
• Track flaky tests, find the cause, and keep the regression suite fast and trustworthy.

AI enabled QA

• Set how the team uses AI in testing, and require human review of everything AI produces before it enters a test suite or a report.
• Use AI assistants and agents, such as GitHub Copilot, Microsoft 365 Copilot, and the Playwright Test Agents, or other similar tools, to draft test plans, test cases, test data, and automation code from requirements and user stories.
• Use AI to find gaps and ambiguity in requirements, summarize failed runs and defect patterns, and rank regression tests by the risk of each change.
• Test AI features in the applications we build, and plan for answers that vary from run to run.
• Check tests written by AI for accuracy, maintainability, and security. Keep confidential data, credentials, and personal information out of prompts and test files, and use only approved tools.

Innovation and leadership

• Challenge the usual way of testing. Pilot new tools and AI techniques, measure whether they help, and share what works across the practice.
• Coach and review the work of QA Practitioners, set goals, and give regular feedback.
• Report on defect leakage, regression automation coverage, test stability, UAT completion, and release readiness.
• Contribute to the CentriLogic QA practice with reusable templates, accelerators, estimating guidance, and QA input to proposals and statements of work.