Embark on a career shaping the future of AI governance and risk management with EY. Join a dynamic team focused on building a better working world through innovation and technology. This client-facing role offers a unique opportunity to impact global brands by addressing complex business challenges in AI risk, auditing, privacy, and security.

As part of our Enterprise Risk practice, you'll dive deep into Artificial Intelligence (AI) Risk Management and Governance. Your expertise will be crucial in areas such as AI auditing, risk and controls assessment, pre-implementation reviews, data privacy, AI application security, and business continuity planning for AI applications. This is a perfect environment to gain extensive experience in complex business transactions and recommend cutting-edge solutions.

Deliver high-quality client services consistently, ensuring work is completed on time and within budget. Proactively monitor progress, manage risks, and maintain clear communication with key stakeholders regarding outcomes.

Cultivate strong client relationships, analyzing and enhancing information systems to bolster security at both procedural and technological levels.

Apply your knowledge of current IT environments, AI models, applications, and industry trends to identify client service issues. Communicate these findings effectively through written correspondence and presentations. Stay informed about evolving business and industry trends relevant to client operations.

Leverage your proven experience in technology and business process internal audit, combined with strong interpersonal skills, to deliver exceptional results in assessing, designing, and supporting the implementation of AI Risk solutions.

Essential qualifications include a bachelor's or master's degree and 3-6 years of relevant work experience. A minimum of 2-4 years in internal audit, risk, or compliance for both business and IT is required, with a solid understanding of AI-related risks and governance frameworks. Specific experience in IT pre- and post-implementation reviews, Model Risk Management, AI compliance, and risk assessments is critical. Familiarity with frameworks like the EU AI Act, COBIT, ISO, NIST, and ITIL is expected. Experience in control monitoring and testing against standards such as PCI DSS and ISO 27001 is also necessary. You should be adept at identifying confidentiality, integrity, and availability deficiencies and evaluating them against industry standards. Experience with IT infrastructure risk assessments, data quality, data privacy, and OS/DB reviews is valuable. Identifying control automation opportunities through analytics platforms is a plus.

Functional understanding of foundation models (LLMs) and their associated risks, alongside awareness of the AI deployment lifecycle, is key. Knowledge of Responsible AI principles, AI Ethics, and AI Assurance is important. The ability to identify process-level risks arising from AI use and develop mitigation strategies is crucial. Relevant industry certifications such as AIGP, ISO 42001, CISA, CISM, CISSP, CRISC, CCSK, or ISO 27001 are beneficial. Excellent communication, documentation, and report writing skills are a must.