AI Test Engineer

Role Overview The AI Test Sr. Engineer II is part of the Software Applications Development Team and is responsible for analysing requirements, designing, and implementing test strategies AI-enabled solutions across mobile, cloud, and analytics platforms. This role emphasizes validating AI/ML models, data pipelines, and intelligent features to ensure accuracy, fairness, security, and regulatory compliance. The AI Test Sr. Engineer will develop and maintain automation frameworks, regression suites, and specialized validation tools for AI systems. Supports product development engineering projects within the assigned area by performing the following duties personally or in collaboration with software developers, data scientists, and cross-functional stakeholders.

Description • Design and implement test strategies that cover accuracy, performance, fairness, bias detection, explainability, robustness, and regulatory compliance of AI systems. • Create automated test frameworks for data pipelines, APIs, and AI components, integrated with CI/CD. • Collaborate with developers, data scientists, product managers, and QA peers, and to identify risks and ensure high-quality AI features. • Test end-to-end workflows involving AI services, data ingestion, pre processing, and decision support tools. • Apply exploratory testing techniques to identify failure modes unique to AI systems (e.g., adversarial inputs, edge cases). • Design and execute test plans in alignment with agile methodology and continuous delivery practices. • Document test coverage, defects, metrics, and model validation results; provide clear reporting to stakeholders. • Support compliance with healthcare regulations, data privacy, and ethical AI practices. • Stay current with AI testing tools, frameworks, and industry best practices.

Expected Areas of Competence (i.e., knowledge, skills and abilities) • Experience testing AI/ML models, data pipelines, and APIs in production-like environments. • Familiarity with bias detection, model drift monitoring, and explainability frameworks (e.g., SHAP, LIME). • Strong background in automation (e.g., Python, PyTest, Playwright, or similar) and data validation using SQL. • Ability to create and maintain robust test documentation, including model validation reports, test plans, and execution metrics. • Excellent written and oral communication skills; ability to translate technical findings into clear business impact. • Self-starter requiring minimal supervision, with strong analytical, planning, and organisational skills. • Effective collaborator and advocate for AI quality across development, product, and compliance teams.

Education/Experience Requirements • Bachelor’s Degree in Computer Engineering, Computer Science, or an engineering discipline with computer science experience required; • 8+ years of experience in Software Quality Assurance