QA Engineer (AI/ML Automated Product Build)

About the position

We are seeking a QA Integration Engineer to join our team and design an AI/ML-based automated testing tool that integrates into our current product suite. The role involves setting up a cutting-edge testing framework for our Dart server-side framework while leveraging AI/ML to enhance efficiency and accuracy. This is a pivotal position that requires technical expertise, creativity, and a willingness to innovate.

Responsibilities

Design and implement AI/ML-based testing automation. Build upon traditional unit testing frameworks to incorporate AI-driven insights and predictive analytics for test case generation and issue diagnosis. Develop and deploy an AI-driven automated testing framework for our Dart backend using tools like dart test and Mockito. Integrate AI to dynamically generate, optimize, and prioritize test cases. Implement real-time feedback loops using AI/ML to identify flaky tests and optimize test execution. Set up arenaflex/CD pipelines to incorporate automated testing results. Utilize ML algorithms to analyze code changes and predict potential areas of failure. Provide actionable reports based on AI-generated data to guide developers. Document the AI/ML testing framework for scalability and ease of use and perform monthly updates to maintain alignment with the evolving codebase and emerging AI technologies.

Requirements

Proven experience in setting up unit testing frameworks for backend systems. Proficiency in Dart programming and testing libraries (e.g., dart test, Mockito). Demonstrable experience with AI/ML tools and libraries (e.g., TensorFlow, PyTorch, scikit-learn) and applying them to software testing. Familiarity with arenaflex/CD tools (e.g., GitHub Actions, GitLab arenaflex, Jenkins). Strong organizational skills and experience in documenting technical frameworks. Ability to implement modular frameworks capable of test case generation, optimization, and reporting; mock and stub Dart backend services; and integrate with existing arenaflex/CD pipelines.

Nice-to-haves

Experience integrating static code analysis tools like SonarQube. Knowledge of real-time monitoring tools for backend systems. Familiarity with AI tools like DeepCode, Codacy, or CodeWhisperer. Experience with AI model retraining, continuous refinement of test cases based on real-time insights, and creating comprehensive guides for onboarding team members.