Test Automation Lead – AI Testing

Enterprise AI QA & Strategy: Define, implement, and own enterprise-wide test automation strategies and quality assurance frameworks tailored for AI/ML models, LLMs, GenAI architectures, and intelligent enterprise systems.

AI Evaluation & Benchmarking: Design and execute automated test suites for AI evaluation, model validation, bias detection, result explainability, prompt validation, adversarial testing (Red Teaming), and prompt-injection safeguards using frameworks like RAGAS, DeepEval, LLM-as-a-Judge, and LangFuse.

Data & Pipeline Validation: Develop robust automated testing for ML training and inference pipelines, verifying data validation, data quality, data drift, and model drift across cloud platforms.

Full-Stack Automation: Implement end-to-end automated UI, API, and performance testing for AI-enabled applications using Playwright, Cypress, Postman, k6, or JMeter, integrating automated quality gates into CI/CD pipelines (Jenkins, GitHub Actions, Azure DevOps).

Technical Leadership & Governance: Lead and mentor global cross-functional QA engineering teams, collaborate with Data Scientists and ML Engineers, champion responsible AI practices, and provide expert consultation on emerging quality engineering technologies.

Comprehensive mastery of Generative AI, RAG pipelines, Agentic AI, and machine learning lifecycles.

Strong programming proficiency in Python, JavaScript/TypeScript, alongside test automation and MLOps tools.

Global healthcare organization dedicated to life-changing innovation with patient-first values.

Competitive global benefits, continuous technical learning opportunities, and inclusive work culture.