Quality Assurance Automation Engineer (Remote Opportunity) - VetsEZ - Tampa, FL

VetsEZ is seeking a Mid-Level QA / Automation Engineer to support the testing, validation, and quality assurance of web-based applications within the Department of Veterans Affairs (VA) environment. This role is responsible for planning, executing, and maintaining both manual and automated test efforts to ensure high-quality, reliable software delivery.

The ideal candidate brings strong experience in test automation frameworks, a meticulous attention to detail, and demonstrated ability to leverage AI tools and techniques to enhance testing efficiency, coverage, and accuracy.

This position requires U.S. citizenship and the ability to obtain and maintain a Public Trust clearance. Candidates must reside in the US.

Responsibilities:
• Plan, design, and execute comprehensive test strategies for web-based applications
• Perform functional, regression, integration, and end-to-end testing across multiple environments
• Develop, maintain, and execute automated test scripts using industry-standard frameworks (Playwright preferred, Selenium acceptable)
• Validate application behavior against functional and technical requirements
• Identify, document, and track defects using Jira (XRay preferred)
• Collaborate with developers, product owners, and cross-functional teams to ensure quality throughout the development lifecycle
• Maintain detailed and structured test cases, ensuring traceability and consistency across releases
• Contribute to test documentation and knowledge sharing using Confluence
• Participate in Agile ceremonies including sprint planning, backlog grooming, and retrospectives
• Support CI/CD pipelines by integrating automated testing into build and deployment workflows

AI-Enabled Testing Responsibilities:
• Leverage AI-assisted tools (e.g., test generation, defect prediction, code analysis) to improve test efficiency and coverage
• Utilize AI-driven approaches for test case generation, prioritization, and maintenance
• Apply machine learning-based validation