AI Risk Management Specialist

S&P Global Mobility • London, ON

3d

About The Position

This role involves maintaining the organization's AI risk taxonomy and assessment methodology, covering safety, fairness, reliability, explainability, robustness, and harmful output risks. The specialist will develop risk evaluation rubrics for AI-specific risk dimensions, create and maintain templates for risk documentation, and support project teams in applying the risk assessment framework. Additionally, the role includes executing periodic independent risk audits, supporting red-teaming and adversarial testing coordination, and collaborating cross-functionally with Engineering and Cybersecurity teams. The company culture is described as one that encourages 'wild growth and working with happy, enthusiastic over-achievers'. Mobility is committed to providing equal employment opportunity (EEO) and reasonable accommodations for qualified individuals with disabilities.

Requirements

• Experience in AI/ML risk management, model risk management, technology risk, or a related analytical function.
• Working knowledge of AI-specific frameworks and legislation (NIST AI RMF, ISO 42001 & 23053, EU AI Act, and the proliferating landscape of US state-level AI legislation).
• Familiarity with risk assessment across safety, fairness, reliability, explainability, and robustness dimensions.
• AI risk taxonomy and assessment methodology maintenance.
• Developing risk evaluation rubrics: bias testing, fairness metrics, explainability, drift, and harmful output.
• Risk documentation: model cards, risk assessments, impact analyses, and risk scorecards.
• Model evaluation and fairness/safety testing.
• Audit execution and independent risk review.
• Cross-functional collaboration with Engineering and Cybersecurity.

Nice To Haves

• Hands-on experience with model evaluation, bias and fairness testing, or AI red-teaming is a plus.

Responsibilities

• Maintains the organization's AI risk taxonomy and assessment methodology, covering safety, fairness, reliability, explainability, robustness, and harmful output risks.
• Develops risk evaluation rubrics for AI-specific risk dimensions (e.g., bias testing protocols, fairness metrics, explainability requirements by use case, drift tolerance thresholds, harmful output tolerances) within the established risk tolerance and acceptance thresholds.
• Develops and maintains templates and standards for risk documentation (model cards, risk assessments, impact analyses, risk scorecards); project teams produce their own documentation using these templates.
• Supports project teams in applying the risk assessment framework and quality gates, escalating high-risk deployments for direct review.
• Executes periodic independent risk audits on a sample basis to verify that federated execution meets the standards; project QAs provide first-line coverage.
• Supports red-teaming and adversarial testing coordination with the Cybersecurity team, focusing on safety, bias, and harmful output dimensions.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed