Internal Audit-Artificial Intelligence, Vice President-Dallas

Goldman Sachs•Dallas, TX

About The Position

As a VP – Artificial Intelligence Auditor, you will provide independent assurance over the firm’s AI control environment, with a focus on Generative and Agentic AI systems across their full lifecycle. The role leads audits of AI platforms and applications, evaluating controls related to data governance, model design, deployment, monitoring, building responsible AI and change management. The VP partners with audit management, project team and stakeholders, to support audit execution, reporting, management updates, and support monitoring for emerging of AI risk and audit methodology for testing.

Requirements

Bachelor's degree in Computer Science, Information Systems, Engineering, or a related quantitative field.
Minimum of 8+ years of experience in technology audit
Minimum 2+ yrs of AI audit experience
Understanding of AI ethics principles, responsible AI frameworks, and relevant data privacy regulations (e.g., GDPR, CCPA).
In-depth knowledge of IT general controls, application controls, cybersecurity frameworks (e.g., NIST CSF, ISO 27001, NIST AIRMF), and data governance principles.
Excellent analytical, critical thinking, and problem-solving skills, with the ability to translate complex technical concepts into clear, concise audit findings.
Exceptional written and verbal communication skills, capable of influencing stakeholders at all levels.

Nice To Haves

Relevant professional certifications such as Certified Information Systems Auditor (CISA), Certified Information Systems Security Professional (CISSP), Certified in Risk and Information Systems Control (CRISC), or ISACA Advanced in AI Audit (AAIA)

Responsibilities

Lead and execute comprehensive technology audits across various domains, including infrastructure, applications, data management, and cybersecurity, with a specialized focus on emerging AI technologies.
Conduct in-depth audits of Generative AI (e.g., Large Language Models) and Agentic AI systems throughout their entire lifecycle covering including AI regulations, This includes evaluating:
Reviewing the provenance, quality, privacy, and bias mitigation strategies for training and inference data used in AI models.
Assessing the rigor of AI model design, testing, validation, and explainability (XAI) frameworks to ensure accuracy, reliability, and interpretability.
Evaluating controls around AI model deployment, performance monitoring, drift detection, versioning, and incident response processes.
Identifying and assessing risks related to AI bias, fairness, transparency, intellectual property, data leakage, and potential for unintended or harmful outputs (e.g., hallucinations in Generative AI).
Examining the design and controls governing autonomous decision-making, interaction protocols, safety mechanisms, and the security of multi-agent systems to prevent unintended consequences.
Evaluate the effectiveness of controls designed to manage technology risks, ensuring compliance with internal policies, industry best practices, and evolving regulatory requirements impacting AI in financial services.
Collaborate effectively with technology and business stakeholders to understand complex systems, identify control gaps, and provide actionable, value-added recommendations.
Prepare high-quality, impactful audit reports and presentations for senior management, clearly articulating findings, risks, and recommendations.
Act as a subject matter expert, providing guidance and mentorship to junior auditors and contributing to the continuous improvement of audit methodologies, particularly in the AI domain.
Stay current with advancements in AI technologies, cybersecurity threats, and the evolving regulatory landscape impacting financial services.