AI Governance Engineer – Remote in Toronto

The AI Governance Engineer is the technical production engine behind the bank's AI standards and controls build-out. Working under the direction of the AI Governance & Controls Lead, this role drafts the standards library, engineers controls as implementable and testable requirements, builds control-to-evidence mappings, and produces the documentation and automation that make governance operational rather than aspirational.

Responsibilities

• Draft and iterate the AI standards library under the Lead's direction: model onboarding and approval, oversight tiers, logging/retention, agentic guardrails, data-classification handling, and acceptable use.
• Engineer each control as a testable requirement: definition, enforcement point, owner, evidence artifact, and validation method.
• Build and maintain obligation-to-control-to-evidence mappings against regulatory guidance and internal policy.
• Contribute to policy-as-code and controls-automation approaches with the platform team where controls can be enforced or checked mechanically.
• Produce evidence artifacts, control attestations, and assessment documentation for deviations, exceptions, and governance reviews.
• Validate platform-generated evidence (audit logs, entitlement records, quota enforcement) against control requirements; document gaps and drive fixes.
• Support deviation and exception lifecycle management: drafting, compensating-control documentation, tracking, and closure evidence.
• Assemble components of examiner-readiness and audit-response packages.
• Support AI Control Group, working group, and committee operations with prepared materials, assessments, and documented decisions.
• Maintain the AI use case and agent registry data quality in partnership with intake and platform onboarding.
• Document governance processes, runbooks, and templates in bank repositories for FTE handover.
• Transfer working knowledge to bank FTEs throughout the engagement.

Skills - Must Have

• Minimum of 5 years' experience in technology governance, IT risk/controls, security governance engineering, or compliance engineering in a technology environment.
• Demonstrated experience writing technical standards, control frameworks, or control documentation that maps to regulatory or policy obligations.
• Working technical knowledge of cloud platforms and modern application patterns: APIs and gateways, identity/RBAC, logging and monitoring, environment separation.
• Familiarity with AI/GenAI systems sufficient to write accurate, enforceable requirements for model access, oversight, and logging.
• Strong technical writing and documentation discipline; able to produce artifacts that survive audit and second-line challenge.
• Experience with GRC processes: exceptions, findings, evidence collection, and remediation tracking.

Nice to Have

• Financial services or other highly regulated industry experience; familiarity with model risk management concepts.
• Experience with policy-as-code, compliance automation, or controls testing automation.
• Familiarity with NIST AI RMF, SR 11-7/SR 26-2 lineage, or comparable AI governance frameworks.
• Azure experience (APIM, Entra ID, Azure Monitor, Key Vault).