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Mobile SDET 2
Location
India
Posted
31 days ago
Salary
0
Seniority
Senior
Job Description
Mobile SDET 2
HighLevel
• Design and develop scalable automation frameworks for mobile applications**• Write clean and maintainable automation scripts using Appium (Android & iOS)**• Execute and manage test runs on BrowserStack or similar cloud platforms**• Integrate automation tests into CI/CD pipelines (Jenkins, GitHub Actions)**• Collaborate with developers and product teams to define test strategy**• Perform functional, regression, and end-to-end testing**• Debug issues, analyze root causes, and ensure timely resolution**• Improve automation coverage and reduce manual testing******AI-Driven Responsibilities**• Leverage AI tools to generate test cases, edge cases, and test data from requirements, PRs, or API specifications**• Use AI to analyze test failures, logs, and screenshots to accelerate debugging and root cause analysis**• Contribute to building or integrating AI-powered utilities such as PR analysis, test impact analysis, or smart test selection**• Continuously explore ways to optimize STLC using AI, reducing regression time andimproving release confidence
Job Requirements
- 3–6 years of experience in QA Automation / SDET**
- Strong experience with Appium (Android & iOS)**
- Proficiency in JavaScript/TypeScript (preferred) or Java**
- Experience with BrowserStack or similar tools**
- Experience with frameworks like WebdriverIO, Mocha, Jest**
- Hands-on experience in API testing**
- Experience with CI/CD pipelines**
- Strong understanding of OOP and test design principles**
- Experience with Git**
- Strong debugging and problem-solving skills****AI-Related Requirements**
- Hands-on experience using AI tools (e.g., ChatGPT, Claude, Copilot) for test case generation, debugging, or automation improvements**
- Understanding of how AI can be applied in test automation, CI/CD, and quality**engineering workflows**
- Ability to validate and refine AI-generated outputs to ensure accuracy and reliability**
- Basic understanding of LLMs, prompt engineering, or AI-assisted workflows in a testing context******
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