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Director, Generative and Agentic AI Model Validation

Job in Toronto, Ontario, C6A, Canada
Listing for: Bank of Montreal
Part Time position
Listed on 2026-06-06
Job specializations:
  • IT/Tech
    Data Scientist
  • Finance & Banking
    Data Scientist
Salary/Wage Range or Industry Benchmark: 100000 - 125000 CAD Yearly CAD 100000.00 125000.00 YEAR
Job Description & How to Apply Below
Final date to receive applications:05/26/2026

Address:100 King Street West Job Family Group:

Audit, Risk & Compliance Are you ready to lead the way in the dynamic world of financial risk management? 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.

Our team values flexibility, collaboration and in-person engagement. 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.

If you’re looking for your next dream job, consider this one in BMO’s ERPM Risk group where every colleague helps protect and grow the bank by providing independent review and oversight of enterprise-wide risks, working together to maintain a risk management framework and fostering a strong risk culture. #ERPMDream Jobs 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.

Key accountabilities include:

Technical Model Validation & Standards 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.

Risk Assessment & Advisory 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.

Stakeholder & Regulatory Engagement 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.

Leadership & Capability Building 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…
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