Top Remote QA Jobs in Tucson, AZ

Drive QA across web and mobile products through manual and automated testing (functional, integration, regression, API, end-to-end). Define acceptance criteria with product, write BDD/Gherkin tests, log and triage defects, maintain automated suites, integrate tests into CI/CD, monitor QA KPIs, mentor engineers, and leverage AI-assisted testing tools to improve coverage and efficiency.

Create and execute test plans, cases, and scripts for features, bug fixes, integrations, and releases. Investigate, document, track, and validate defects and customer issues. Communicate release changes and draft release notes. Use AI-assisted tools when appropriate and contribute to QA process and standards improvements.

Manually test Shopify eCommerce stores for design, functionality, and responsive behavior. Verify pages against Figma and project requirements, use DevTools to inspect and debug, document and report bugs, collaborate with developers/PMs/designers, and suggest fixes for recurring issues to ensure flawless launches.

Lead QA for a OneStream ERP/EPM implementation: plan and execute system, integration, and UAT testing; create and run test cases; log and triage defects; perform regression and end-to-end validation; maintain test evidence and support deployment readiness, hyper-care, and post-go-live stabilization.

QA Engineer responsible for testing Manhattan Active WMS implementations and integrations. Create test strategies, plans, and cases; perform functional, integration, system, regression, and UAT testing; validate warehouse processes, RF/mobile transactions, and APIs; log defects in Jira/Azure DevOps; support SIT, Go-Live, and Hypercare in Agile teams.

Own QA for web and mobile releases: write and run manual and automated tests (web, mobile, API), build test frameworks, improve CI, track issues, mentor teammates, and influence requirements and quality processes.

Part-time QA Analyst reviews emails, invoices, confirmations, and system outputs to verify financial and operational data accuracy. Identify inconsistencies, duplicates, and mapping errors, flag anomalies, and report reproducible issues with context to engineering to maintain data integrity and reliable financial outputs.