The AI Governance Manager will lead strategic initiatives for AI oversight, ensuring ethical deployment and regulatory compliance across the enterprise. They will manage data integrity, oversee AI model performance, and foster collaboration between technical and business stakeholders.
AI Governance Manager
Summary
We are seeking a seasoned professional to lead our strategic initiatives in Artificial Intelligence oversight and data integrity. This pivotal role is designed to ensure the ethical deployment, regulatory compliance, and robust management of AI systems across the enterprise. The ideal candidate will bridge the gap between advanced data engineering, comprehensive data governance frameworks, and the emerging landscape of responsible AI, driving a culture of transparency and accountability in all algorithmic operations.
Responsibilities
Spearhead the end-to-end implementation of AI governance frameworks, ensuring alignment with organizational policies and external regulatory standards.
Oversee the monitoring and assurance of AI models, utilizing specialized tools to track performance, bias, and adherence to ethical guidelines throughout the model lifecycle.
Champion the principles of responsible AI by establishing protocols for transparency, fairness, and explainability in all automated decision-making processes.
Manage Master Data Management (MDM) strategies to guarantee the accuracy, consistency, and reliability of data feeding into AI systems.
Maintain comprehensive metadata repositories, data catalogs, and lineage tracking to ensure full visibility into data sources and transformations.
Direct enterprise-wide data governance efforts, fostering collaboration between technical teams and business stakeholders to uphold data quality and security.
Leverage a strong background in data engineering to design scalable governance architectures that support complex AI workloads.
Requirements
Requirements:
Minimum of 10 years of professional experience within the IT Services sector.
Proven expertise in Enterprise Data Governance, with a track record spanning 7 to 10 years.
Demonstrated hands-on experience (3–4 years) in implementing AI governance solutions.
Deep proficiency in Master Data Management (MDM) principles and practices.
Strong command of AI assurance methodologies, including model monitoring and governance tooling.
Extensive knowledge of metadata management, data cataloging, and data lineage tracking.
Solid foundation in Data Engineering to support technical governance requirements.
Ability to articulate and enforce standards for AI transparency, fairness, and explainability.
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