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AI Model QA QC

This outlines the governance and oversight responsibilities of an AI Project Manager throughout the model development lifecycle. Rather than focusing on technical coding, the role emphasizes quality control by establishing rigorous testing protocols that cover accuracy, security, and ethical fairness. Managers must implement configuration management to maintain a clear history of model versions, datasets, and training parameters to ensure full traceability. Additionally, the position involves monitoring performance metrics and facilitating independent peer reviews to mitigate technical and regulatory risks. By enforcing standardized coding practices and automated validation pipelines, the AI Project Manager ensures that models are secure, reproducible, and ready for real-world deployment.