Lead AI & Technology Risk Auditor

AllstateMcCullom Lake, IL
Hybrid

About The Position

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. Specialists serve as key contributors to audit transformation, 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. This role requires a strategic thinker who can develop internal and leverage external networks, apply sound judgment, and deliver high-quality audit results. The Lead AI & Technology Risk Auditor takes personal accountability to ensure audits are performed with proficiency and plays a vital role in developing future audit leaders by providing coaching, guidance, and effective delegation.

Requirements

  • 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)
  • 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).
  • 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)
  • Reliable internet is required, with minimum speeds of 50 MB download and 5 MB upload.

Nice To Haves

  • 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).
  • 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)

Responsibilities

  • 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.
  • Demonstrate excellence in agile sprint execution by managing test progress, updating documentation status, and flagging blockers.
  • 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 (1) sprint reviews that communicate early observations, refine direction, and align with stakeholder priorities and (2) 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 areas such as 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 large language model (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 (e.g., continuous monitoring, document review, predictive risk scoring) to improve audit quality, coverage, and efficiency.
  • Stay current on evolving AI regulatory requirements, industry standards, and risk frameworks (e.g., NIST AI Risk Management Framework, IEEE AI ethics standards, and applicable state/federal AI legislation) and incorporate them into audit planning and testing.

Benefits

  • Comprehensive technology setup, including a laptop, monitors, headset, keyboard, and mouse.
  • Monthly connectivity reimbursement to help offset internet costs for eligible remote employees.
  • Opportunity to shape the future of protection.
  • Support for causes that mean the most to you.
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