• Design and develop automated metadata harvesting architecture • Build Python/SQL-based data pipelines for metadata extraction from diverse systems • Integrate AI tools for intelligent metadata classification and tagging • Implement Human-in-the-Loop (HITL) validation workflows for AI-assisted harvesting • Deploy harvesting automation across enterprise systems for scalable metadata capture • Develop drift detection and alerting mechanisms for metadata change management • Create and maintain technical documentation for all automation components • Support empirical testing in sandbox environments for technology evaluations • Optimize harvesting processes to achieve efficiency gains • Coordinate with QA teams on automation quality standards • Troubleshoot and resolve pipeline issues across production environments