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This is a hybrid role in Toronto

The Manager, AI Enablement is a hands-on individual contributor responsible for enabling AI use-cases and production-grade AI capabilities across Canada P&BB Data & Analytics. The role partners closely with Product Owners, Business Architecture, Data & Analytics, and Technology teams to translate business needs into scalable, enterprise-grade AI solutions, while ensuring alignment to the capability roadmap and long-term architecture strategy.

Key Responsibilities

AI Use Case Delivery

• Partner with Product Owners to define, prioritize, and execute AI use cases aligned to business priorities and roadmap

• Translate business problems into implementation-ready AI solutions, including workflows, data requirements, and models

• Investigate new technologies and vendor solutions for AI use-cases

Architecture & Roadmap Alignment

• Partner with Business Architect to align AI initiatives to capability roadmap and target architecture

• Ensure technology selections and implementation approaches support long-term strategy and scalability

• Provide feedback into roadmap based on delivery insights and technical feasibility

Cloud & Technology Delivery (AWS / Azure)

• Collaborate with platform, engineering, and other teams to design robust AI environments

• Ensure alignment with enterprise standards and cloud strategies

Cross-Functional Collaboration

• Work across business, data, and engineering teams to deliver production-ready AI outcomes

• Gather and translate business needs into clear functional and non-functional requirements (e.g., SLAs, data freshness, controls, auditability)

• Act as a bridge between business stakeholders and technical teams, ensuring clarity and alignment throughout delivery

MLOps & Platform Enablement

• Partner with Technology Teams to enable production-grade MLOps pipelines, including model development, deployment, monitoring, and optimization

• Support model lifecycle management (registry, versioning, CI/CD, environment promotion, reproducibility)

• Support creation of scalable model inference capabilities across batch and/or real-time environments

Qualifications

5-8+ years of experience in AI or analytics delivery

Strong hands-on Python/PySpark experience development for production

Experience with AWS and/or Azure ecosystems

Proven experience delivering production AI solutions

Strong ability to translate business needs into technical requirements and delivery plans

Solid understanding of the MLOps lifecycle, including:

• Model registry and versioning

• CI/CD and deployment strategies (e.g. canary, shadow)

• Monitoring and reproducibility

The above represents BMO Financial Group’s pay range and type.

Salaries will vary based on factors such as location, skills, experience, education, and qualifications for the role, and may include a commission structure. Salaries for part-time roles will be pro-rated based on number of hours regularly worked. For commission roles, the salary listed above represents BMO Financial Group’s expected target for the first year in this position.

BMO Financial Group’s total compensation package will vary based on the pay type of the position and may include performance-based incentives, discretionary bonuses, as well as other perks and rewards. BMO also offers health insurance, tuition reimbursement, accident and life insurance, and retirement savings plans. To view more details of our benefits, please visit: