AI Operations (RAIOps) Lead - 82383

Position Title: AI Operations (RAIOps) Lead

Line of Business: Wealth Management - AI Center of Excellence

Duration: 11 months (Possibility of Extension)

Location: Downtown Toronto - Hybrid 4 days in office

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Role Overview

The Responsible AI Operations (RAIOps) Lead within Wealth Management is responsible for operationalizing Responsible AI practices across the Wealth AI portfolio. This position ensures that AI solutions are ethical, explainable, compliant, and aligned with both regulatory requirements and business objectives. The RAIOps Lead collaborates with cross-functional teams to embed Responsible AI into every stage of the AI lifecycle, from ideation to production.

Key Responsibilities

• Develop, implement, and maintain Responsible AI frameworks, policies, and controls for Wealth Management in alignment with CDAO and enterprise AI
• Conduct risk assessments and monitor AI models for bias, drift, and regulatory compliance.
• Oversee operational reliability, security, and ethical use of AI systems across the AI lifecycle.
• Collaborate with business, compliance, legal, and technology teams to align AI solutions with organizational guidelines, policies and regulatory expectations.
• Lead incident management and escalation for AI-related issues.
• Drive continuous improvement in Responsible AI practices, including automation, monitoring, and reporting.
• Liaise with Responsible AI, Risk and Governance forums
• Present use cases for approval to the applicable forums
• Ensure all risk and responsible AI questionnaires are completed reviewed, submitted and updated on the agreed cadence

Must Have Requirements:

• Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field.
• 5+ years’ experience in AI operations, governance, or risk management within financial services.
• Demonstrated experience developing and implementing Responsible AI frameworks.
• Track record of leading cross-functional teams and driving organizational change.
• Excellent communication and relationship management abilities.

Nice-To-Haves:

• Deep knowledge of AI/ML technologies, regulatory standards, and ethical frameworks.
• Stakeholder management and leadership skills.
• Proven ability to communicate complex technical concepts to non-technical audiences.
• Experience with program/project management and team leadership.
• Technical proficiency in AI/ML operations, monitoring, and automation tools (e.g., MLOps platforms, model monitoring solutions, risk assessment tools).
• Familiarity with cloud platforms (Azure, AWS, GCP) and data governance tools.
• Analytical and problem-solving skills, especially in risk mitigation and compliance

Interviews:

45 minute panel interview - virtual