Senior QA Engineer

AirHelp is the world’s #1 flight compensation company, combining proprietary travel technology and passenger intelligence to support millions of travelers throughout their journey.

Key Metrics & Services

• Compensation: Over 3 million passengers successfully paid compensation to date.
• Protection (AirHelp+): More than 15 million passengers protected during flights.
• Flight Tracking: Free mobile app exceeded 1 million downloads within its first year.
• Industry Partnerships: Active collaborations with over 140 online travel agencies (OTAs), airlines, and insurers.

Operational Scale & Infrastructure

• In-House Engineering: Dedicated technology teams developing scalable travel-tech solutions.
• Legal Network: The world's largest network of specialized air passenger rights lawyers.
• Global Team: A 400+ person team operating across 5 offices worldwide.

• At least 5 years of experience as a QA Engineer, QA Automation Engineer, Developer in Test, or similar senior role.
• Practical knowledge of Playwright and modern end-to-end testing.
• Experience in API testing using Postman, Bruno, or similar tools.
• Experience integrating automated tests with GitHub Actions or similar CI/CD pipelines.
• Interest and experience with using AI tools for testing, debugging, test generation, and analysis.
• Ability to collaborate with developers, perform risk analysis, and balance automation with exploratory testing and delivery speed.
• Ownership of work area, clear communication, and influence on senior engineers without formal authority.
• Good command of English in speaking and writing.

Nice to have:

• Experience with Postman, risk analysis, monitoring tools, and GitHub Actions.

• Create and evolve test automation strategies for critical Document and Communication flows in the Claiming Experience area.
• Design, build, and maintain automated tests using Playwright, Postman, Bruno, and CI/CD pipelines.
• Shorten feedback loops and support fast validation of changes before and after deployment.
• Support developers in owning quality through testing patterns, joint test design, and sharing best practices.
• Utilize AI tools, AI agents, and automated analysis for test generation, debugging, and regression analysis.
• Develop quality observability and collaborate with developers, product managers, and stakeholders on risk assessment.

Expected results after 12 months:

• Increased confidence in daily deployments and improved automated coverage.
• Faster regression verification through quicker and more accurate tests.
• AI-supported testing strategies reducing manual verification.
• Quicker failure investigation using traces from Playwright, logs, Sentry, Grafana, Kibana, CI/CD, and AI.