Director, Generative and Agentic AI Model Validation

BMO•Toronto, ON

2d•Hybrid

About The Position

BMO is seeking a talented and experienced professional to join our Model Risk Management Team as a Director, Generative and Agentic AI Model Validation. As a Director in our second-line governance and control function, you will play a pivotal role in overseeing the execution pillar of model risk management across a large range of models supporting critical business and risk management mandates. You will lead the execution of the model risk framework activities through the model lifecycle, ensuring that it aligns with regulatory expectations and BMO's commitment to excellence in risk management. This position is located in Toronto and offers flexibility with a hybrid work arrangement where the successful candidate will spend at least 3 days per week on-site and the other days remote. The Director, Generative and Agentic AI Model Validation will be responsible for the independent validation and effective challenge of AI models using advanced techniques including Generative AI, AI agents and agentic AI. As part of the Model Risk Management (MRM) team in the second line of defence, the Director is accountable for assessing model design, data, performance, robustness, effectiveness, weakness and limitations, and thus the associated model risk and controls in place to mitigate identified risk. This role is a hands-on technical leader, accountable for setting validation standards, leading complex and novel model reviews, acting as a subject matter expert in AI model validation, and driving innovation and application of AI within MRM to improve effectiveness and efficiency.

Requirements

Typically 9+ years of relevant experience and post-secondary degree in related field of study or an equivalent combination of education and experience.
Expert knowledge of GenAI and/or AI agent, and evolving validation practices for AI models and other emerging model types.
Expert knowledge of evolving regulatory requirements impacting AI model.
Seasoned expert with extensive industry knowledge.
Technical leader viewed as a thought leader for innovation.
Verbal & written communication skills - Expert.
Analytical and problem solving skills - Expert.
Influence skills - Expert.
Collaboration & team skills; with a focus on cross-group collaboration - Expert.
Able to manage ambiguity.
Data driven decision making - Expert.

Nice To Haves

Graduate degree in a quantitative field, Computer Science, Engineering or related field of study preferred.

Responsibilities

Develop, maintain, and enhance validation standards, testing expectations, and review methodologies for AI models, including GenAI and AI agents, aligned with Model Risk Management principles.
Lead independent validation and effective challenge of AI models used across the enterprise, with a focus on GenAI, AI agents and agentic AI.
Lead the research and development for validation of new types of models.
Measure the effectiveness of AI model validation and ongoing monitoring practices, recommending enhancements as required.
Conduct independent analysis to assess AI model risks associated with new business initiatives and third‑party engagements, recommending actions or escalation as appropriate.
Provide advice and guidance to the first line of defence on AI model testing, monitoring, and remediation, delivering credible and technically grounded challenge.
Identify emerging risks, issues, and trends related to AI models to inform senior management decision‑making.
Work closely with other second‑line and compliance functions (e.g., Technology Risk, Data Risk, Legal) to ensure clear role delineation and alignment.
Act as the primary contact for internal and external stakeholders, including regulators, on matters related to AI model validation.
Represent the AI model validation portfolio in internal and external audits, regulatory reviews, and examinations.
Communicate complex and abstract technical concepts clearly and succinctly to senior and non‑technical audiences.
Recommend measures to improve organizational effectiveness.
Drive innovation and application of AI and GenAI in MRM to improve effectiveness and efficiency.
Attract, retain, and develop top technical talent within the AI model validation team.
Drive high performance through coaching, feedback, and accountability, addressing performance issues as required.
Influence cross‑functional collaboration and ways of working across teams and groups.
Recommend strategic priorities, resource requirements, and execution roadmaps for the AI model validation capability.
Foster a culture aligned with BMO’s values, purpose, and commitment to diversity and inclusion.
Act as a trusted advisor to senior leaders on AI model risk, validation outcomes, and strategic initiatives.
Apply expert judgment and creative problem‑solving to address complex, ambiguous, and interdependent issues.
Network with external peers and industry forums to stay current on best practices and regulatory expectations in AI model validation practices.
Support enterprise strategic initiatives through expert technical input and execution leadership.
Broader work or accountabilities may be assigned as needed.