Quality Engineer II

About the role

RLDatix is on a mission to transform care delivery worldwide, ensuring every patient receives the safest, highest-quality care. Through our innovative Healthcare Operations Platform, we’re connecting data to unlock trusted insights that enable improved decision-making and help deliver safer healthcare for all. RLDatix (RLD) is on a mission to help raise the standard of care…everywhere. Trusted by over 10,000 healthcare organizations around the world, our solutions help improve health and care. Our applications ensure that patients receive the best and safest care while supporting the providers who deliver it. Joining TeamRLD means being part of a global effort of over 2,000 team members in making a difference in healthcare…every day.

Responsibilities

• Play a hands-on role in ensuring the quality, reliability, and usability of RLDatix applications that support critical healthcare workflows.
• Design and execute comprehensive test plans using both manual and automated methods; validate new features throughout the sprint; identify defects; maintain automation coverage; and support release readiness across a fast-moving product environment.
• Balance manual testing with automation, contribute to regression efforts, and use AI tools responsibly to improve productivity, test coverage, and quality outcomes while growing toward deeper technical contribution over time.
• Test development items throughout each sprint; plan and execute manual and automated regression testing before releases; validate new features against functional requirements, user workflows, and customer expectations.
• Document defects clearly, partner with developers to resolve issues, verify fixes through release, and participate in release readiness activities including regression cycles, code‑freeze validation, and release‑night support when needed.
• Create, maintain, and expand automated tests using Playwright; validate JSON payloads, API requests and responses, and error handling; use MySQL and MS SQL Server queries to troubleshoot issues and validate data.
• Use AI tools responsibly to support test case creation, test maintenance, and automation productivity, while reviewing