Managing Director, Data & AI Governance

About the role

Accountabilities

• Operationalize and mature enterprise Data Governance and AI Governance frameworks, aligned with Information Security, Enterprise Risk Management, and AI strategy.
• Serve as a first-line operational leader and SME in risk forums; manage Data and AI risk within risk appetite and maintain escalation pathways.
• Ensure enterprise adherence to OSFI Guidelines, DAMA-DMBOK, and FIFAI principles.
• Oversee metadata harvesting, Critical Data Element lineage, data classification, data quality monitoring, and data retention and disposition.
• Work with technical custodians to enforce least-privilege access, dynamic masking, and obfuscation in golden-source environments such as DEEP.
• Establish and report mandatory AI controls, including high-risk agentic AI runtime controls, Policy-as-Code, Human-in-the-Loop checkpoints, non-human identity scoping, and immutable WORM trajectory logging.
• Embed shift-left governance into the software development lifecycle using the AI & RAI Canvas, automated risk tiering, and threat modeling at intake and ideation.
• Partner with Cyber Security and Model Risk Management on continuous telemetry, trajectory logging, loop execution limits, and manual kill-switch protocols.
• Support AI strategy execution, education and literacy, responsible innovation, ethical data use, and risk awareness across all three lines of defense.

Skills, experience and requirements

• Bachelor’s or Master’s degree in Computer Science, Computer Engineering, Risk Management, Business Administration, Information Management, or a related field.
• At least 10 years of progressive leadership experience in data governance, risk management, or AI governance; financial services or regulated-sector experience is preferred.
• In-depth knowledge of OSFI E-21, E-23, B-10, FIFAI, NIST AI RMF, and privacy/data protection standards.
• Hands-on experience with DAMA-DMBOK, enterprise data catalogs, metadata/lineage platforms such as Collibra, and cloud analytics platforms such as Google Cloud BigQuery/DEEP.
• Understanding of AI lifecycle management, LLMs, agentic AI architectures, Model Context Protocol, and Policy-as-Code enforcement.
• Ability to communicate complex risk, compliance, and governance concepts clearly to executive leadership and cross-functional teams.

Work arrangement

• Hybrid work arrangement averaging one to two days on-site per week; this may change with business priorities.

About ATB