Sr. Manager, AI Audit & Automation

This role engineers the AI-enabled future of Internal Audit. The Sr. Manager, AI Audit & Automation designs, builds, and deploys production-grade AI and automation solutions that transform how audit work is planned, executed, and evidenced. The role combines hands-on AI engineering with deep integration into audit workflows, governance standards, and regulatory requirements. 

This is a building role. This role is measured by what is created, what is adopted, and what is auditable not by hours logged or meetings attended. The successful candidate builds working systems, trains audit teams on the tools being built, and continuously improves the production environment based on real engagement feedback. Results are measured in deployed tools, adopted workflows, and documented audit efficiency gains. 

The position reports to the Director, Technology Assurance, and partners closely with IT, Information Security, and the CAE to deliver audit-specific AI capabilities at enterprise scale. 

• →Partner with audit teams to define high-impact AI use cases, translating audit objectives into scalable technical solutions owing design and deployment end to end. 

• →Lead the build and rollout of AI-powered applications and automation frameworks across audit workflows, ensuring alignment with enterprise AI governance and applicable regulatory requirements. 

• →Own end-to-end technical delivery of the SOX ITGC Self-Assess Agents and similar AI workflows from prototype through development, UAT, and production environments in partnership with IT. 

• →Manage Claude API and enterprise LLM integrations — prompt engineering, structured output design, error handling, and performance optimization. 

• →Build and maintain data pipelines connecting audit systems to AI workflows, including Active Directory, access management platforms, ERP data, and audit management tools. 

• →Design and execute full population audit testing using Alteryx, Python, or SQL — replacing sample-based testing where data access permits. 

• →Develop continuous monitoring scripts that flag control exceptions in real time rather than at periodic testing intervals. 

• →Establish performance metrics and continuously optimize deployed solutions to produce measurable, auditable improvements in audit efficiency and control evaluation quality. 

• →Produce and maintain comprehensive technical documentation: model artifacts, system architecture diagrams, validation protocols, and data lineage records that satisfy both internal audit standards and external scrutiny. 

• →Drive adoption within Internal Audit by designing user-centric implementations, translating technical concepts for non-technical audiences, and delivering hands-on training to ensure durable workflow integration. 

• →Evaluate emerging AI, machine learning, and LLM technologies on an ongoing basis to assess applicability and scalability within Internal Audit environments. 

• →Serve as the technical lead for audit management system integration, overseeing scalable connectivity of AI tools, workflow automation, and enterprise platforms. 

• 4+ years in data science, AI/ML, analytics, or software engineering. 

• Hands-on production deployment of AI/ML solutions. 

• Demonstrated experience building or managing AI agents and automation frameworks. 

• Enterprise LLM tool experience — Claude, ChatGPT, Perplexity, or equivalent — including prompt engineering and structured output design. 

• CI/CD, containerization, or MLOps implementation in an enterprise environment. 

• Cloud platform experience in AWS, Azure, or GCP. 
• Experience with large-scale data platforms such as Snowflake. 
• Python and SQL proficiency. 

• Functional HTML, CSS, and JavaScript for frontend development and dashboarding. 

• REST API integration — consuming and orchestrating external APIs. 

• Git — version control, branching, pull requests, and code review. 

• Working knowledge of model governance, validation, and responsible AI practices. 

• Understanding of AI ethics principles and applicable data privacy regulations (GDPR, CCPA, and equivalent). 

• Ability to translate complex technical concepts into audit-relevant findings and stakeholder communications. 

• Audit and domain knowledge 

• Working knowledge of SOX IT General Controls  

• Understanding of evidence sufficiency standards and workpaper documentation requirements. 

• Familiarity with PCAOB AS 2605 or equivalent assurance standards. 

• Experience deploying automation or analytics tools within an audit, risk, or compliance function. 
• Ability to translate audit requirements into technical specifications independently.
• Bachelor's degree in Computer Science, Engineering, Statistics, Information Systems, or a related field is required. Advanced degree (MS or PhD) in Machine Learning, Statistics, or Computer Science is a plus. 

• Internal Audit, Risk, Compliance, or Financial Services experience. 

• Familiarity with audit management systems or GRC platforms. 

• Experience integrating AI tools with enterprise systems and platforms. 

• Big 4 or advisory firm experience in audit technology practice. 

• Digital commerce, e-commerce, or sports and entertainment industry background. 

• Experience in a PE-backed or high-growth technology company environment. 

• CISA, AAIA, CRISC, CISSP 

• AWS, Azure, or GCP Machine Learning Specialty, or data science certifications.