Lead and execute specialized audits of Generative AI (LLMs) and Agentic AI systems throughout their lifecycle, ensuring compliance with emerging global AI regulations. Review the provenance, quality, and privacy of consumer datasets used for training and inference, ensuring mitigation of bias in personalized marketing and loyalty programs. Assess the rigor of AI model design, validation, and explainability (XAI) to ensure accuracy in automated retail decisions (e.g., inventory forecasting or dynamic pricing). Evaluate controls around deployment, performance drift detection, and incident response for AI agents interacting with customers or vendors. Identify risks related to "hallucinations," data leakage, intellectual property, and fairness in automated hiring or credit-offer systems. Collaborate with Data Science, Engineering, and Legal teams to identify control gaps and provide actionable, value-added recommendations that support retail agility. Prepare high-quality, impactful audit reports for the VP of Internal Audit and senior leadership, translating complex technical risks into business impact. Serve as the internal consultant for AI risk, staying current on the evolving regulatory org landscape (e.g., EU AI Act) and its impact on the retail sector. Assess the completeness and effectiveness of AI governance frameworks, including model inventory, risk tiering, approval workflows, and alignment to enterprise policies. Evaluate controls over third-party AI solutions, including vendor governance, model transparency, data usage, model cards, training disclosures, usage limitations, contractual safeguards, and audit rights for internally developed and third‑party AI model Design and evolve audit programs, control frameworks, and testing techniques specific to GenAI and Agentic AI, integrating them into the Internal Audit risk assessment and audit lifecycle. Assess whether AI‑enabled systems introduce risks to financial reporting, including pricing accuracy, inventory valuation, revenue recognition inputs, and management review controls. Bachelor's degree in Computer Science, Data Science, Information Systems, or a related quantitative field. 8+ years of experience in technology audit, IT risk management, or data science. Minimum 2+ years of direct experience auditing or governing AI/Machine Learning environments. In-depth knowledge of IT general controls (ITGC), NIST AI Risk Management Framework, and data privacy regulations (e.g., GDPR, CCPA). Exceptional ability to influence stakeholders and explain technical AI risks to non-technical business leaders.

Certifications:

CISA, CISSP, or specialized AI credentials (e.g., ISACA AI Fundamentals/Audit, IAPP Certified AI Governance Professional). Experience auditing consumer-facing technologies, e-commerce platforms, or automated supply chain systems. Proficiency in Python or SQL to perform independent data analysis or model testing. Experience aligning AI risks to enterprise risk management (ERM), operational risk, and internal control frameworks. Familiarity with model risk management (MRM), AI governance councils or ethics boards, and regulatory exams or external audit interactions related to emerging technology. Please note that you do not need to qualify for all requirements to be considered. We encourage you to apply if you can meet most of the requirements and are comfortable opening a dialog to be considered. Ability to sit and work at a computer keyboard for extended periods of time Ability to stoop, kneel, bend at the waist, and reach daily