Senior Software Development Engineer Test
3 days ago
Styli
Established in 2019 by Landmark Group, Styli is the GCC e-commerce getaway for a trendy fashion. Scaling fast and offering over 40,000 styles for men, women and kids, sourced from across the globe, Styli aims to bring the latest in fashion to our customers
About the Role
We are looking for a highly skilled Tooling and
AI Automation Engineer (SDET-2)
to join our Automation team—not in a traditional application development capacity, but as a specialist focused on building internal tools, test intelligence platforms, dashboards, and AI-driven test enablement frameworks
Job Title: Tooling & AI Test Automation Engineer
Experience Level: 6-13 years
Required Skills- Mandatory
• Proficiency in Java, Python, , or similar scripting languages.
• Hands-on experience with dashboarding tools (Grafana, Kibana, Superset, or custom solutions using ).
• Working knowledge or experience with Mabl, TestRigor, or any AI automation tool.
• Strong understanding of test automation frameworks (e.g., Pytest, Playwright, Cypress, Selenium).
• Experience integrating tools with CI/CD pipelines (Jenkins, GitHub Actions, GitLab CI).
• Familiarity with databases (SQL, NoSQL) and working with test data at scale.
• Experience in building REST APIs or microservices for internal use
Key Responsibilities
• Test Automation Development: Build and maintain robust, scalable test automation frameworks for API, web, and mobile platforms.
• Design, develop, and maintain internal tools that enhance automation capabilities, CI/CD integration, and test data visualization.
• Build intelligent dashboards for real-time reporting of test results, release quality metrics, and defect analytics.
• Develop AI/ML-based solutions to optimize test case prioritization, test suite reduction, flakiness prediction, and self-healing scripts.
• Integrate tools and dashboards with CI pipelines (e.g., Jenkins, GitHub Actions) and test frameworks (Selenium, Playwright, etc.).
• Work closely with SREs, and DevOps teams to ensure tools are scalable, performant, and well-adopted.
• Create APIs, microservices, or CLI tools that support testing workflows, artifact management, and defect traceability.
• Continuously evaluate new AI/ML advancements and incorporate them into test engineering practices.
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