Design, build, and train machine learning models specifically to minimize test maintenance requirements and adapt to frequent application changes
Develop AI systems that can automatically detect and repair broken tests when application interfaces change
Create self-healing test frameworks that reduce manual maintenance intervention
Leverage full-stack development expertise to build end-to-end testing solutions that seamlessly integrate with application code
Develop backend services that support AI model training, deployment, and continuous improvement
Create frontend interfaces for monitoring test health, maintenance needs, and cross-team visibility
Implement API layers that connect testing intelligence with CI/CD pipelines and development workflows
Serve as a technical bridge between development and QA teams, with the credibility of full-stack expertise
Establish shared metrics and visibility tools that help both teams understand test health and maintenance needs

8+ years software architecture experience with full-stack development capabilities
4+ years focused on AI/ML applications, particularly in automation contexts
Deep expertise in machine learning frameworks with emphasis on models that reduce maintenance overhead
Proven experience training and deploying ML models that improve automation resilience
Strong proficiency in Playwright and modern test automation frameworks with focus on maintainability
Advanced programming skills in full-stack technologies including: Frontend: JavaScript/TypeScript, React/Angular/Vue Backend: Node.js, Python, Java or similar
Experience with self-healing test frameworks and intelligent test object recognition
Extensive background in test maintenance challenges and solutions
Experience with test automation in environments with frequent UI/API changes

Principal AI Automation Engineer

Key skills