Software QA Engineer

About the Role

As a Software QA Engineer, you will work closely with engineers and product teams to make sure our software works as intended and remains reliable as it changes. You will help understand requirements, identify risks, develop and execute tests, investigate issues, and clearly communicate what you find.

You will use Claude Code as a daily tool to help create and refine test scenarios, explore edge cases, understand unfamiliar areas of the application, investigate failures, support test automation, and help us continuously improve how we approach quality. We expect Software QA Engineers to use AI to make their work faster and more thorough while applying their own judgment to the results. AI can help you think through a problem, but you are still responsible for deciding what needs to be tested, whether the output is useful and correct, and when a different approach is needed.

Because we work with healthcare and human services data, good data-handling practices are also part of the job. You will be expected to follow Radicle Health's HIPAA and data-handling guidelines, including when using AI-assisted tools. Testing and investigation should use synthetic, mocked, or appropriately de-identified data rather than real customer PHI. When a testing need appears to require production data or PHI, you are expected to stop and escalate rather than making that decision on your own.

This is a mid-level engineering role. You will have support from experienced Software QA Engineers while building the product knowledge and technical depth needed to take increasing ownership of testing and product quality.

What You'll Do

• Review requirements and acceptance criteria to understand expected behavior and identify unclear requirements, missing scenarios, edge cases, and potential risks.

• Create, maintain, and execute test cases covering expected behavior, failure conditions, regression risks, and real user workflows.

• Use Claude Code as part of your daily testing workflow to generate and refine test scenarios, identify possible edge cases, investigate defects, understand application behavior, and assist with automated testing.

• Write clear and specific prompts that give AI tools the context needed to produce useful test scenarios, analysis, or code, and refine those prompts when the results are incomplete or off target.

• Review and validate AI-generated tests, analysis, and code rather than assuming generated output is correct or complete.

• Follow Radicle Health's data-handling and HIPAA guidelines during testing and investigation, including when using Claude Code or other AI-assisted tools. Use synthetic, mocked, or de-identified data in place of customer PHI and escalate when a testing need appears to require access to sensitive production data.

• Identify, document, and track defects with clear reproduction steps, expected and actual behavior, supporting evidence, and enough context for the engineering team to investigate efficiently.

• Investigate issues using tools such as SQL, browser developer tools, application logs, APIs, source code, automated tests, and AI-assisted analysis.

• Use SQL to validate application data, investigate unexpected behavior, and support testing across product workflows.

• Work with QA Automation Engineers to prioritize, and at times build and maintain, automated tests using tools such as Playwright, focusing automation on repetitive, high-value, and regression-prone workflows.

• Contribute automated tests that run as part of our CI/CD pipeline and help maintain confidence as changes move toward production.

• Work closely with engineers to reproduce issues, validate fixes, understand root causes, and identif