Mid-Level QA Automation Engineer

🏢 omniops
📍 EgyptFull-timeOn-site
📅 Posted: 6d ago🔄 Updated: 6d ago
CV%
✨ AI Summary
OmniOps is seeking a Mid-Level QA Automation Engineer with 3-5 years of experience to join their Riyadh-based team. The role focuses on validating their AI inferencing platform's core functionalities, integrations, and security. Key responsibilities include designing test cases, developing automation scripts using Playwright Python, conducting integration and security testing, and performing API and database testing. The engineer will also integrate automated tests into CI/CD pipelines and manage defects in JIRA.
Required Skills
Information Technology
Test AutomationJupyter
Requirements
Requires 3-5 years of professional software quality assurance experience. Must have strong hands-on experience with Playwright and proficiency in writing SQL queries for Postgres, testing RESTful APIs, and verifying multi-service integrations. Familiarity with basic web security fundamentals, CI/CD integration, and AI/data science concepts is expected.
Description
OmniOps is a Riyadh-based technology solutions provider, serving organizations across Saudi Arabia and beyond. With offices in Jordan, Egypt, and Morocco, we specialize in empowering businesses to migrate and scale their AI technology infrastructure confidently, achieving a high level of maturity in their digital landscapes. Our comprehensive services and products guarantee seamless cloud migration, scalability, and management, ensuring optimal performance and consistent reliability for our valued partners.Role OverviewFocus on validating the core functionalities, integrations, and basic security postures of our data science and AI inferencing platform. You will be responsible for designing test cases, writing reliable automation scripts, verifying data flows between microservices, and ensuring that services like JupyterHub, ticketing systems, and CI/CD pipelines function seamlessly and securely.Key Responsibilities Test Design & Execution: Design, maintain, and execute comprehensive test cases for complex workflows (e.g., cluster creation, resource allocation, and notebook integration). Automation Development: Develop, maintain, and extend automated test suites. Implement reliable UI automation scripts primarily using Playwright Python. Integration Testing: Conduct detailed integration testing to verify seamless data flow, component communication, and dependency handling between the ticketing system, service allocation engines, and JupyterHub or NotebookLLM. Security Testing: Perform basic security testing, including validating authentication/authorization mechanisms, verifying role-based access control (RBAC) for different user tiers, checking API endpoint vulnerabilities, and ensuring secure communication protocols. API & Database Testing: Perform detailed testing of REST APIs and validate data integrity within Postgres databases. Manual & Exploratory Testing: Conduct manual exploratory, functional, and regression testing as needed. CI/CD Integration: Integrate automated test suites into existing pipelines (GitLab CI, GitHub Actions, or Jenkins). Defect Management: Log and track bugs effectively in JIRA, ensuring clear and reproducible steps. Reporting & Collaboration: Prepare test execution reports, ensure proper test coverage before releases, and collaborate with product and development teams to clarify requirements. Qualifications & Technical Skills Experience: 3–5 years of professional experience in software quality assurance. Automation Stack: Strong hands-on experience with Playwright (typescript preferred). Familiarity with other frameworks like Selenium, Cypress, pytest, TestNG, or JUnit is a plus. Integration & Backend Skills: Proficient in writing SQL queries for Postgres, testing RESTful APIs using tools like Postman, and verifying multi-service integrations. Security Knowledge: Understanding of basic web security fundamentals (OWASP Top 10, JWT authentication, OAuth, and access control). DevOps & Tools: Experience working with GitLab, Artifact Registry, and containerized environments (Docker/Kubernetes basics). AI/Data Science Familiarity: Good knowledge of AI systems development, basic AI concepts, and familiarity with data science tools like JupyterHub.
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🎯 Overalli74%
⚡ Skillsi85%
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Ontology Match: 85.0
Matched:✓ Requirements Matching✓ Ontology Skills Mapping
📜 Eligibilityi49%
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Local: 19600%
🏗️ Career Fiti91%
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Seniority: 91.0
📋 Requirementsi67%
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Domain: 67.0
🔥 Motivationi78%
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Title Fit: 78.00