Description

Typical task breakdown: - Define the AI vision and architecture for the testing function. - Identify testing activities that can be improved with AI, including: test case generation, test data creation, automated test maintenance, defect prediction, root cause analysis, log and failure analysis, requirements-to-test traceability, risk-based test prioritization, intelligent regression selection - Design and implement AI-enabled frameworks for: functional testing, API testing, UI automation, performance testing, security testing support, exploratory testing augmentation - Partner with QA, developers, DevOps, product managers, and data teams to embed AI into CI/CD and quality engineering workflows. - Evaluate and recommend AI/ML, GenAI, and test automation tools. - Establish standards for AI governance, privacy, security, explainability, and responsible usage in testing. - Create architecture for integrating LLMs, test repositories, defect systems, observability tools,...