Lead AI & Technology Risk Auditor

Role Description

The Lead AI & Technology Risk Auditor is a senior-level audit professional and subject matter expert who leads complex audits in high-risk or emerging technology domains, with a particular focus on artificial intelligence, generative AI, and data-driven systems. This role designs tailored audit methodologies, engages with senior leaders to understand risk exposure, and drives innovation through the use of AI, data science, and automation.

• Independently lead complex, agile technology and business audits with objectivity.
• Manage the creation and execution of audit programs, including drafting testing plans and acceptance criteria.
• Apply critical thinking data analytics, and AI-assisted audit techniques to evaluate evidence.
• Communicate effectively with audit clients through sprint reviews and audit reports.
• Build and maintain strong, trust-based relationships with IT and business leaders.
• Provide coaching and feedback to audit team members.
• Demonstrate strong business acumen by applying knowledge of Allstate's operations.
• Assess controls over the development, deployment, and monitoring of generative AI applications.
• Support department initiatives to improve audit quality, coverage, and efficiency.
• Stay current on evolving AI regulatory requirements and incorporate them into audit planning.

Qualifications

• 5 or more years of experience.
• 1 or more years of experience auditing, implementing, or assessing AI/ML systems, data governance frameworks, or advanced analytics platforms (Preferred).

Requirements

• Core certifications (CPA, CA, CISA, CIA, or CFE) are required for all new Lead Consultant and above roles, and must be obtained within 18 months if not already held.
• AI or data-related certifications are a plus (e.g., ISACA Certificate in AI Fundamentals, ISACA Advanced in AI Audit [AAIA], AWS/Azure AI certifications, or relevant data science credentials).

Preferred Skills & Knowledge

• Familiarity with AI/ML concepts including supervised/unsupervised learning, neural networks, natural language processing, and generative AI architectures.
• Working knowledge of Python, SQL, or similar tools for data extraction, analysis, and visualization.
• Familiarity with or high interest in AI governance principles, including fairness, accountability, transparency, explainability, and data privacy.
• Awareness of AI/ML platforms (e.g., Azure ML Studio, Azure AI Foundry, AWS Bedrock, AWS SageMaker, GCP BigQuery, GCP Vertex AI, Open AI and other LLM foundational models, M365 Copilot Studio).

Travel Requirements

• Minimal travel required (approximately 15%).

Compensation

Compensation offered for this role is 0.00 - 0.00 annually and is based on experience and qualifications.