QA Engineer

• Use AI tools like Cursor to rapidly generate test cases from requirements, user stories, and code diffs.
• Build and maintain automated end-to-end test suites using frameworks like Cypress, Playwright, or Selenium, with AI assistance to speed up development and catch edge cases.
• Integrate AI-driven static analysis, code coverage tools, and anomaly detection into CI/CD pipelines.
• Define and manage test strategies for new product features with a focus on AI-augmented speed and accuracy.
• Use LLMs and agents to simulate user behavior for broader scenario coverage.
• Continuously evaluate and implement AI-powered QA platforms to improve regression, smoke, and exploratory testing.
• Collaborate with engineers on shift-left testing practices, pairing during development to catch issues early.
• Monitor application performance, errors, and logs using tools like Sentry, DataDog, or equivalent — augmented by AI-powered alerting and triage.
• Contribute to defining AI-first QA best practices, playbooks, and tooling standards across the team.
• Experience with AI agents for QA (e.g., auto-test authors, regression explorers, or defect triagers).
• Familiarity with backend testing, including API-level test automation (Postman, REST Assured, etc).
• Exposure to healthcare or regulated industries.
• Knowledge of performance testing tools (e.g., k6, JMeter) or visual regression testing suites.

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