Mohamed Moheyeldin

Selected engagements: U.S. Department of Veterans Affairs (VA) | Internal Revenue Service (IRS)

This role combines hands-on automation engineering with technical leadership in federal delivery environments. I lead framework direction and team execution while continuing to design UI and API tests, diagnose unreliable automation, integrate quality signals into CI/CD, and improve the systems teams use to make release decisions.

• Led a team of five automation engineers, establishing scalable test strategies, resource planning, and automation standards.
• Designed and documented Cypress and Playwright automation frameworks for UI and API testing with asynchronous handling, retry logic, and robust assertions.
• Automated UI and API regression suites using Playwright tracing, network mocking, and auto-waiting to improve failure diagnostics and reduce flaky execution.
• Built CI/CD pipelines with GitHub Actions and Cypress Dashboard, including artifact management, parallel execution, and dynamic environment provisioning.
• Used AWS EC2, Aurora DB, and S3 to support on-demand test environments and scalable test execution.
• Implemented automated defect triage through Jira API integration and risk-based failure prioritization.
• Created test dashboards with Allure and Elastic Stack for trend analysis, failure-pattern recognition, and anomaly detection.
• Delivered automation training covering asynchronous execution, event-driven automation, and API-first testing approaches.
• Developed data-provisioning utilities using JSON, Excel with Apache POI, and SQL-driven injection for mock responses and contract testing.
• Configured Selenium Grid for parallel cross-browser testing and JMeter performance benchmarks.
• Improved test-code branching, deduplication, parallel execution, and retry strategies to reduce false positives in CI.
• Defined SLAs and KPIs for test execution, defect turnaround, coverage thresholds, and CI/CD success rates.

I focused on moving quality feedback earlier in the delivery lifecycle by treating automation as an engineering product rather than a collection of scripts. The work connected browser, API, visual, authentication, cloud-environment, and CI concerns into maintainable test systems that could provide faster and more useful release feedback.

• Architected GitHub Actions CI/CD pipelines integrating Cypress Dashboard and AWS for automated execution and rapid feedback.
• Designed modular smoke and regression suites with JavaScript, Cypress, and Mocha, including flaky-test mitigation.
• Integrated Applitools Eyes visual regression testing across multiple resolutions, devices, and browsers.
• Developed Cypress and Postman API suites with contract testing, schema validation, and dynamic data-driven assertions.
• Applied parallel execution, network stubbing, and headless testing to reduce test run time while maintaining accuracy.
• Implemented OIDC and Okta MFA automation in Cypress for SSO-based applications.
• Managed AWS EC2, Aurora DB, and S3 resources with AWS CLI to support scalable test environments.
• Integrated Cypress Dashboard analytics, video recording, and automatic retries into CI/CD workflows.

This role established the testing foundation that continues to shape my automation work: understanding business intent, designing risk-based coverage, investigating behavior across browsers and environments, communicating defects clearly, and partnering with delivery teams through release validation rather than treating testing as a final checkpoint.

• Performed manual exploratory, functional, and regression testing of web applications across multiple platforms.
• Created test plans, test cases, and acceptance criteria aligned with business and functional requirements.
• Executed cross-browser and responsive UI testing on Chrome, Firefox, Safari, and Edge.
• Collaborated with developers, analysts, and product owners to refine acceptance criteria and validate business logic.
• Tracked and prioritized defects in Jira, partnered on root cause analysis, and verified fixes.
• Ran smoke, regression, and sanity testing across development, QA, UAT, and staging environments.
• Supported pre- and post-deployment validation, hotfix verification, sanity testing, and production monitoring.
• Mapped scenarios to business and functional requirements to identify validation gaps and improve coverage.