Role Summary: We are looking for a technically sophisticated Senior QA Engineer to lead the quality assurance strategy for our Health Claim Management Solution. You will move beyond manual testing to build a robust Automated Testing Framework that covers functional, security, and performance aspects. You will act as the "Gatekeeper of Production," ensuring that our Java Spring microservices and AI pipelines meet the strict security (OWASP) and reliability standards required by the UAE and KSA markets.
Key Responsibilities:
- Test Automation Framework (The Core):
- Design and maintain a scalable automation framework using Java (RestAssured/Selenium) or Python (Pytest/Playwright).
- Implement "Shift-Left" testing: Write automated tests that run immediately after a developer commits code, integrating them into the CI/CD pipeline (GitHub Actions/Jenkins).
- Develop End-to-End (E2E) tests for critical RCM workflows (Claim Submission -> Adjudication -> Remittance).
- API & Microservices Testing:
- Focus 70% of testing efforts on the API Layer. Use RestAssured or Postman/Newman to validate JSON contracts, HTTP status codes, and error handling (RFC 7807 compliance).
- Implement Contract Testing (e.g., using Pact) to ensure microservices (Backend vs. AI vs. Frontend) do not break each other during updates.
- Security Testing (DevSecOps):
- Execute Dynamic Application Security Testing (DAST) using tools like OWASP ZAP or Burp Suite to identify vulnerabilities (SQL Injection, XSS, IDOR) before release.
- Validate strict data privacy controls (KSA PDPL/HIPAA), ensuring PII is masked in logs and API responses.
- Conduct regular penetration testing scenarios on the authentication/authorization layers (OAuth2/JWT).
- Performance & Load Testing:
- Design load testing scenarios using k6 or JMeter to simulate high-volume claim submissions (e.g., 10,000 claims/hour).
- Identify bottlenecks in database queries or API latency and collaborate with the Backend team to resolve them.
- AI & Data Quality:
- Collaborate with the Data Architect to validate Data Integrity in PostgreSQL and Vector Databases.
- Create test cases for AI/ML outputs (e.g., verifying that the "Claim Rejection Prediction" score falls within expected confidence intervals).