Senior QA Automation Engineer – AI Applications UK

Details

• Design and maintain automated test suites, evaluation scenarios, metrics, and test datasets for AI-powered features
• Automate QA workflows using Python and CI/CD (e.g., GitHub Actions, Jenkins), leveraging AI-powered testing tools to improve test development, maintenance, and coverage
• Create and maintain test harnesses for AI services, applications, and APIs
• Perform API testing for AI services and backend systems
• Define quality strategy and acceptance criteria for AI-powered applications across functional, API, integration, and AI/ML features
• Test AI/ML applications and machine learning models from a product and user perspective
• Evaluate AI/ML model outputs for correctness, consistency, and expected application behavior
• Define structured rubrics that translate qualitative findings into measurable evaluation gates
• Build quality gates for CI/CD and deployment pipelines, including automated regression and integration testing
• Mentor teams on QA automation best practices and consistent quality standards for AI-powered applications
• Contribute to multi-team projects and codebases, ensuring code quality and consistency
• Participate in code reviews and provide constructive feedback to peers
• Document and present findings and ideas across the company
• Bachelor’s degree in Computer Science, Engineering, or equivalent experience
• 5+ years of professional experience in software quality assurance, test automation, or software engineering
• Strong programming skills in Python, with experience in test automation
• Hands-on experience using AI-powered testing tools or AI coding assistants to improve test automation, productivity, and quality
• Experience with CI/CD tools and processes
• Familiarity with popular CAD environments and tooling
• Proficient in automation and UAT test suites/frameworks
• Experience designing QA frameworks or platforms used by multiple teams
• Excellent problem-solving skills and attention to detail
• Strong communication and collaboration skills
• Understanding of software architecture and design patterns
• Ability to work in an Agile development environment
• Experience testing AI/ML applications or validating machine learning models
• Experience with data validation tooling (e.g., Great Expectations) or labeling workflows
• Familiarity with ML frameworks (e.g., PyTorch, TensorFlow)
• Experience with data pipelines and orchestration tools (e.g., Airflow, Metaflow)
• Knowledge of MLOps practices (e.g., model monitoring, drift detection, deployment validation)
• Knowledge of ML evaluation methods, metrics, and benchmarking
• Passion for learning new technologies and improving existing systems
• Experience with cloud providers (e.g., AWS, Azure, Google Cloud Platform)
• Experience testing AI/ML services in production environments
• Knowledge of experiment tracking tools (e.g., Comet, MLflow, Weights & Biases)
• You demonstrate initiative to provide solutions and to learn and develop new technologies
• Comfortable building QA systems from scratch and writing maintainable automation
• You enjoy learning and collaborating across global locations
• You are comfortable working in newly forming ambiguous areas
• You are comfortable building scalable and maintainable QA automation frameworks that will be relied on by others
• You effectively leverage AI-powered tools to improve testing workflows and engineering productivity
• You can communicate well with others