Inernal Audit Intern (AI & Analytics)

FJ Management•Salt Lake City, UT

13d•Onsite

About The Position

FJ Management (FJM) is a privately held, Utah-based holding company whose businesses include Maverik (convenience retail and fuel), Big West Oil (petroleum refining), and other operating businesses. Our Internal Audit team provides independent assurance and advisory services across all FJM businesses. Our work spans store operations, fuel and inventory, pricing and promotions, labor and payroll, facilities, regulatory and environmental compliance, third-party risk, finance and accounting, and information technology. AI is built into how we work: our audit management platform is connected to AI tools, we maintain a shared library of prompts for specific audit tasks, and we are building a knowledge base from the results of our work. We hold AI-assisted work to the same standards of accuracy, evidence, and confidentiality as everything else we produce. We are looking for an intern who enjoys learning unfamiliar subjects, asking thoughtful questions, and finding practical solutions. You do not need to arrive as an auditor, accountant, or software developer. We are more interested in how you approach a problem, use the resources available to you, and determine whether your answer is reliable. You will work alongside our auditors and our Data Analytics & Automation team on real engagements across the business. Part of your time will support audit projects directly. The rest will go toward improving how the team works: finding tasks AI can do better, building and testing the approach, and helping the team adopt it. In return, you will see a wider range of businesses than most internships offer (retail, refining, transportation, and corporate functions), apply AI to professional work under the review of experienced auditors, and gain a clear view of how a company identifies and manages risk.

Requirements

Currently pursuing a bachelor's or master's degree in any field.
Demonstrated hands-on experience using AI/LLM tools to complete meaningful work (coursework, jobs, or personal projects).
Ability to commit to approximately 20 hours per week.
Practical AI proficiency: Hands-on experience using AI/LLM tools to accomplish meaningful tasks, including the ability to break a problem into steps, write clear prompts, refine an approach when results fall short, and explain how the final output was checked.
Critical thinking and attention to detail: Ability to question assumptions, recognize inconsistencies, distinguish evidence from speculation, and determine when more information is needed.
Curiosity and resourcefulness: Willingness to learn unfamiliar business processes and tools, research questions independently, try different approaches, and ask for help when appropriate.
Clear communication and collaboration: Ability to explain ideas and results in understandable language, write organized documentation, listen to others, and incorporate feedback.
Reliability and organization: Ability to manage assigned tasks, meet commitments, communicate obstacles early, and follow through.

Nice To Haves

Coursework in Information Systems, Computer Science, Accounting, Finance, Data Analytics, or a related field.
Experience with data analysis tools such as SQL, Python, R, Alteryx, or ACL.
Experience with scripting, low-code tools, or version control (e.g., Git) to build repeatable workflows.
Experience organizing data, researching unfamiliar topics, or improving a process.

Responsibilities

Support audit projects: Assist with planning and performing audits under the guidance of the audit team. Help understand business processes, gather supporting information, identify potential risks, and evaluate whether procedures and controls are working as intended. Help draft walkthrough documentation and risk and control matrices.
Turn interviews into usable records: Use AI tools to convert meeting and interview transcripts into structured discussion records, reconcile what different people said about the same process, and identify gaps, inconsistencies, and follow-up evidence requests.
Analyze data: Work with the Data Analytics & Automation team to organize and analyze business data (for example, transaction, pricing, inventory, or payroll data) to test controls and identify exceptions or trends.
Prepare clear documentation: Organize evidence and document work performed, results, and conclusions so another team member can understand and review the work. Assist with drafting audit findings and reports and help track remediation of open issues with business owners.
Collaborate across the business: Participate in meetings, ask questions to understand how work is performed, follow up on information requests, and communicate progress and results professionally.
Build and improve AI-assisted workflows: Identify repetitive or time-consuming steps in audit work, then design, test, and document AI-assisted approaches the team can adopt. Help develop and maintain the team's library of reusable audit prompts, testing them against real examples and refining them when results fall short.
Validate AI-generated work: Check AI output against source evidence, compare results across AI models where useful, flag errors or unsupported conclusions, and document how AI was used so a reviewer can follow and rely on the work.
Build the team's knowledge base: Help organize and classify information from audit results and business discussions into a structured knowledge base so the team can find and reuse what it has learned.
Support AI adoption beyond audit: Assist with advisory projects that help other business teams design and test AI-assisted workflows for their own processes.
Exercise sound judgment: Protect confidential information, follow company AI use and data handling requirements, and recognize when a task requires additional guidance or expertise. Take ownership of the final work product.
Perform other related duties and support team projects as assigned.