• Design and execute test plans for A.I and Machine Learning driven features including classification, summarization, anomaly detection, and autofill systems • Develop Python-based automation and evaluation scripts to validate model performance, reliability, and output quality • Test LLM-based features for accuracy, guardrail effectiveness, hallucination risk, and behavior under edge cases • Validate data pipelines, input/output transformations, and model integration points across Keeper’s platform • Conduct regression testing on ML models and AI workflows to ensure reliability across releases • Test enterprise-scale behavior analysis features driven by data from ARAM, PAM, and session recordings • Validate security, privacy, and zero-trust requirements for AI model interactions and data handling • Collaborate with ML engineers and cross-functional teams to identify defects and improve model behavior • Analyze logs, metrics, and model outputs to detect anomalies, performance issues, or silent failures