QA QE Lead/Architect

Mandatory Skills Playwright with TypeScript (Strong TypeScript coding experience) BDD automation using Cucumber Strong experience with .NET Core / .NET Framework applications API automation using Rest Assured or RestSharp Hands-on experience using AI-assisted development tools such as GitHub Copilot, Claude, Gemini, or similar AI coding assistants for test automation development Experience debugging, reviewing, validating, and optimizing automation code generated by AI assistants to ensure maintainability, reliability, and adherence to coding standards Mobile testing using Appium with cloud platforms such as Sauce Labs, Perfecto, or BrowserStack. Exposure to Applitools, Jira integrations (AssertThat BDD, Zephyr, Xray), and Service Virtualization is a plus. Job Responsibilities Minimum 15+ years of experience in building automated solutions to cover UI frontend, middle tier, and backend interfaces and services Leads the design and implementation of enterprise test automation frameworks, methodology and tool integration for all teams Provides automation expertise, training and coaching to team members Determines range and depth of activities required for developing or customizing complex test automation frameworks, researching and onboarding automation tools for IT Deliver a robust automation framework built upon established and proven open source or commercial tools to support Agile/Scrum development, DevOps and CI/CD Design and architect modular and reusable automated testing solutions that satisfy client requirements Research, evaluation, and deployment of new test tools Trains teams to implement expanded automation coverage by adding automated environment validation, smoke and functional test scripts to CI/CD pipeline Identifies and directs the implementation of test automation related improvements that positively impact software delivery across the enterprise Be familiar with various automated tests tools for both front end and back end testing Ability to lead workshops, including the gathering/documenting of requirements and use-cases and recommendation of envisioned processes Ability to assess functional and technical gaps in designs Support continuous improvement processes, analyzing problems and recommending actions for effective resolution Ability to adapt to a fast paced continually changing business and work environment while managing multiple priorities Design, develop and maintain API automation frameworks supporting authentication, request/response validation, schema validation, and integration with UI automation. Provide automation leadership, mentoring, technical guidance, and code reviews for automation engineers. Effectively utilize AI-assisted development tools to accelerate automation development while ensuring generated code meets enterprise coding, quality, and security standards. Promote automation best practices and continuous quality engineering across Agile development teams. Preferred / Nice to Have Experience implementing AI-driven end-to-end Quality Engineering across the Software Development Lifecycle (SDLC), including: Jira story grooming and review Acceptance criteria validation Test case generation BDD feature file generation Test automation development Test execution and reporting End-to-end traceability between requirements, test cases, automation, defects, and execution results Experience working with AI-powered automation workflows, intelligent test generation, and AI agents that improve software quality and engineering productivity. Experience with cross-browser automation testing using Playwright across Chromium, Firefox, WebKit, and Microsoft Edge. Experience with Visual AI testing using Applitools. Experience with Jira integrations such as Zephyr, Xray, and AssertThat BDD. Experience with Service Virtualization tools. Experience with cloud execution platforms such as Sauce Labs, BrowserStack, or Perfecto. Experience validating backend systems using SQL and database queries. Experience with Git, GitHub, Azure DevOps, and modern source control practices. Exposure to prompt engineering and AI-assisted software development best practices.