Senior Quality Assurance Engineer

Institute of Foundation Models

Role

Key responsibilities

• Design test plans and cases for AI applications, APIs, and platform features; build automated test frameworks for models, data pipelines, and software, primarily in Python.
• Evaluate AI outputs for correctness, fairness, robustness, and consistency; work with cross-functional teams to define metrics and acceptance criteria.
• Conduct manual and exploratory testing; perform end-to-end tests across distributed systems, APIs, databases, web applications, and model inference pipelines.
• Test performance and develop CI/CD pipelines for repeatable testing.
• Track and report defects and quality metrics, drive root-cause analysis, and contribute to quality standards, practices, and documentation.

Academic qualifications

• Bachelor’s degree in Computer Science, Software Engineering, AI, or a related technical field required.
• Master’s degree or equivalent experience in AI systems, software testing, or quality assurance preferred.

Required experience

• Extensive software QA, test automation, and complex-system validation experience.
• Strong Python and hands-on experience with PyTest or a similar test automation framework.
• Knowledge of AI/ML testing challenges, including nondeterministic outputs, dataset biases, and model evaluation metrics.
• Experience testing distributed systems, REST APIs, cloud-native applications, and microservices.
• Familiarity with CI/CD tools such as Jenkins, GitLab CI, or GitHub Actions.
• Analytical attention to detail, edge-case identification, communication, and multidisciplinary collaboration.

Preferred experience

• AI model testing, including LLMs, computer vision, or multimodal models; TensorFlow, PyTorch, or Hugging Face.
• Data QA, dataset validation, annotation workflows, cloud platforms, Docker, Kubernetes, and open-source QA contributions.
• Arabic proficiency for linguistic, data, or regional validation.