Audit and validate data labeling outputs, provide structured feedback and hands-on training to annotators, monitor workflows and escalate issues, help apply and improve guidelines, and identify patterns in human and model outputs to maintain high-quality AI training data.

Lead automation testing efforts, design frameworks, mentor teams, ensure software QA, and drive continuous improvement for clinical trial software.

Design, build, and maintain automated test frameworks and scripts. Lead test strategy, planning, and execution across functional, load, integration, security, server-side, and ETL testing. Create test artifacts, run automated tests, analyze results, report defects, participate in CI/CD, code reviews, and agile ceremonies, and drive issue resolution.