Lead AI & Technology Risk Auditor

Overview

At Allstate, great things happen when our people work together to protect families and their belongings from life’s uncertainties. 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 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.

Specialists contribute to audit transformation by creating scalable frameworks for auditing new technologies such as cloud-native platforms, machine learning systems, generative AI and large language models, agentic AI, and AI-enabled decision-making platforms. They evaluate AI governance, responsible AI practices, and emerging AI risks to ensure Allstate's AI adoption is secure, ethical, and well-controlled. They influence audit strategy, develop team capabilities, and act as technical mentors, ensuring the audit function remains future-ready and delivers meaningful value to Allstate.

• Independently lead complex, agile technology and business audits with objectivity, applying advanced project management skills to guide scrum teams, manage timelines, identify blockers, and ensure timely resolution of audit issues.
• Manage the creation and execution of audit programs, including drafting testing plans and acceptance criteria, performing walkthroughs, identifying controls, and executing testing procedures for complex processes with limited guidance.
• Apply critical thinking, data analytics, and AI-assisted audit techniques to evaluate evidence, identify root causes, assess risk levels, and recommend control enhancements or process improvements. Leverage tools such as Python, SQL, or visualization platforms to perform full-population testing, anomaly detection, and pattern analysis where appropriate.
• Communicate effectively with audit clients through sprint reviews that communicate early observations, refine direction, and align with stakeholder priorities and audit reports that clearly communicate findings, risks, and actions.
• Build and maintain strong, trust-based relationships with IT and business leaders, and actively support Internal Audit's relationship management efforts across the enterprise.
• Provide coaching and feedback to audit team members, supporting their development in control identification, test execution, documentation, AI literacy, data analytics adoption, and strategic thinking.
• Demonstrate strong business acumen by applying knowledge of Allstate's insurance and non-insurance operations, control environment, and interdepartmental dynamics to audit execution and insights.
• Assess controls over the development, deployment, and monitoring of generative AI and LLM-based applications, including prompt engineering safeguards, output validation, hallucination risk, data privacy in training sets, and third-party AI service provider oversight.
• Support department initiatives (process improvement, change leadership, functional expertise) and advance AI, automation, and analytics to improve audit quality, coverage, and efficiency.
• Stay current on evolving AI regulatory requirements, industry standards, and risk frameworks (e.g., NIST AI RMF, IEEE AI ethics standards, and applicable state/federal AI legislation) and incorporate them into audit planning and testing.

• 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)

• This job does not have supervisory duties.

• 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 AAIA, AWS/Azure AI certifications, or relevant data science credentials).

• 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 Sage Maker, GCP Big Query, GCP Vertex AI, OpenAI and other LLM foundational models, M365 Copilot Studio)

• Minimal travel required (approximately 15%).

• Compensation offered for this role is $98,100 - $150,500 annually and is based on experience and qualifications.

Note:

The candidate(s) offered this position will be…