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Quality Assurance Automation Engineer

Unlock employer Abu Dhabi, United Arab Emirates Posted: 30 Sep 2025

Financial

  • Estimate: $60k - $90k*
  • Zero income tax location

Accessibility

  • Office Only
  • No Relocation Support
  • Visa Provided

Requirements

  • Experience: Senior
  • English: Professional

Position

We are seeking a Quality Assurance Engineer with strong automation skills to support testing efforts across our AI-driven platforms. In this role, you will be responsible for ensuring the functional accuracy, performance, and quality of features, while also contributing to the validation of AI model outputs, training data quality, and the overall user experience across web and API-based systems.

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Work Conditions:

  • Contract: 12 months, extendable
  • On-site work

Key Responsibilities:

  • Design, write, and execute test cases to validate features, APIs, and end-to-end system integrations.
  • Develop and maintain automated test scripts using Java-based frameworks (e.g., Selenium, TestNG, or similar).
  • Conduct manual and exploratory testing for AI model outputs and user workflows.
  • Validate training datasets, detect anomalies, and evaluate model-generated content.
  • Log and track defects with comprehensive documentation using bug tracking tools.
  • Collaborate closely with Machine Learning, Development, and Automation teams to define test strategies and acceptance criteria.
  • Contribute to regression testing cycles and final release validations.

Required Skills & Qualifications:

  • 5+ years of professional experience in QA or software testing.
  • Proven experience in QA automation using Java.
  • Solid understanding of Agile methodologies, QA processes, and test lifecycle management.
  • Hands-on experience with test management tools (TestRail, Zephyr) and defect tracking tools (JIRA, Azure DevOps).
  • Strong experience with API testing tools such as Postman.
  • Excellent analytical skills and attention to detail.

Preferred (Nice to Have):

  • Exposure to AI/ML concepts, particularly around testing LLM outputs, computer vision, or NLP systems.
  • Experience validating training data quality and evaluating model behavior in production environments.
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