AI-Driven QA Engineer for Automated Testing

Jobs in JS

Menlo Park (CA)

Hybrid

USD 130,000 - 140,000

Full time

3 days ago
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Benefits offered by this job

Equity opportunities
Unlimited vacation
Parental leave 16 weeks
Healthcare coverage
401k plan

Job summary

Twin Health is seeking an AI Automation QA Engineer to join our hybrid team in Menlo Park. The role focuses on delivering comprehensive regression test coverage for complex web and mobile apps, with emphasis on AI-driven test automation and back-end validation.

Ideal candidates have 3+ years in QA automation, strong coding skills, and experience with Playwright or similar tools. Responsibilities include test plan design, model evaluation, and cross-functional collaboration to ensure a top-tier

Qualifications

  • 3+ years of QA engineering experience focused on test automation.
  • Experience testing web UIs and mobile apps (iOS/Android/Flutter).
  • Experience with AI-driven regression automation.
  • Strong programming skills in JS, Python or Java.

Responsibilities

  • Derive comprehensive end-to-end regression test plans with stakeholders.
  • Design and maintain AI-driven automated regression tests for web and mobile apps.
  • Contribute to evaluation coverage of internally developed models.
  • Develop AI-driven testing strategies and data generation for testing scenarios.
  • Collaborate with Devs, PMs, and UX to ensure outstanding user experience.

Skills

QA engineering
AI-driven automation
JavaScript/Java/Python
communication

Education

Bachelor's degree in Computer Science

Tools

Playwright
Appium
Selenium
Maestro
SQL

Job description

Twin Health is seeking an AI Automation QA Engineer to join our hybrid team in Menlo Park. The role focuses on delivering comprehensive regression test coverage for complex web and mobile apps, with emphasis on AI-driven test automation and back-end validation.

Ideal candidates have 3+ years in QA automation, strong coding skills, and experience with Playwright or similar tools. Responsibilities include test plan design, model evaluation, and cross-functional collaboration to ensure a top-tier

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