10 and above years of experience in software testing, with at least 5 years in test automation architecture — including designing intelligent, data-driven automation solutions for both traditional and AI-powered applications.

1. Automation Tools & AI Testing Strong hands-on experience with multiple automation tools and frameworks (Selenium, Cypress, Playwright, Appium, Rest Assured, Robot Framework, etc.), along with proven exposure to AI-assisted test generation, self-healing automation, and autonomous test execution platforms.

1. Programming & AI/ML Integration

Proficiency in Java, Python, JavaScript/TypeScript, C#, or equivalent languages — including leveraging these for AI model testing, data preprocessing, test dataset generation, and integration with ML pipelines.

Custom Framework Development:

Proven expertise in building custom test automation frameworks across diverse platforms, including:

• Frameworks supporting AI-based decision-making and ML model validation
• Automated model validation integrated within CI/CD pipelines
• Continuous Training (CT) and Continuous Model Evaluation (CME)
• Regression suites covering both software components and ML models

Analytical & Problem-Solving Skills:

Strong analytical, debugging, and problem-solving capabilities — including experience analysing test failures, model drift, and quality signals across complex distributed systems.

Testing Strategy & Leadership:

Experience in defining, driving, and executing testing initiatives — particularly for AI/ML products — with a strong ability to influence quality practices across the engineering organisation.

Communication & Stakeholder Management:

Excellent communication, leadership, and stakeholder management skills, with a track record of providing technical guidance to peers on automation best practices, test coverage strategy, and shift-left/shift-right testing approaches.