The Process Engineer, Internal Audit is the architect of the modern audit function. This role is not about performing audits; it is about designing the systems that perform them. You will engineer, automate, and continuously optimize audit workflows by integrating Generative AI, agentic orchestration, and process engineering principles. Your goal is to move the department from point-in-time manual testing to a continuous assurance model that provides real-time risk insights.
Responsibilities:
Workflow Deconstruction: Analyze and map complex end-to-end audit processes (Risk Assessment through Issue Remediations) to identify automation-first opportunities.
Lean Audit Design: Apply Lean/Six Sigma principles to eliminate waste in the audit lifecycle, such as manual data entry, redundant evidence requests, and administrative overhead.
Scalable Solutions: Design standardized, modular workflow patterns that can be reused across Financial, IT, and Operational audit domains.
Intelligent Augmentation: Build and deploy AI-assisted workflows using Vellum AI, Copilot Studio, and Claude 3.5/4 to automate:
Control Mapping: Automatically mapping disparate business processes to COSO/NIST frameworks.
Automated Walkthroughs: Using AI to summarize meeting transcripts and draft narrative documentation.
Anomaly Narrative Generation: Converting complex data exceptions into plain-English audit findings for reports.
Library Management: Develop and maintain a Prompt Registry and Agent Library to ensure consistency in how AI interacts with sensitive audit data.
Agentic Workflows: Design Agentic automations in Microsoft Power Automate or Make.com that can reason through exceptions, route approvals, and update GRC platforms (e.g., AuditBoard, Workiva) without human intervention.
Tool Mastery: Advanced deployment of DataSnipper for automated document matching (e.g., matching 1,000s of Invoices to POs in seconds) and population integrity testing.
Real-time Risk Dashboards: Design and maintain Power BI or Tableau visualizations that provide a live Risk Heatmap based on automated testing results.
AI Governance: Ensure all AI solutions are explainable and meet corporate Model Risk Management (MRM) and data privacy (GDPR/CCPA) standards.
Validation Controls: Embed Human-in-the-Loop checkpoints into every automated process to ensure AI-generated output is validated by a subject matter expert.
You'd be a good fit with:
Education & Experience
Education: Bachelor's degree in Industrial Engineering, Information Systems, Data Science, or Accounting with a heavy technical focus.
Experience: 5-8+ years in Audit Transformation, Process Excellence, or Business Systems Engineering.
Technical Stack (2026 Proficiencies)
AI Platforms: Hands-on experience with LLM orchestration (Vellum, LangChain, or Copilot Studio).
Automation Hubs: Advanced proficiency in Power Automate, Zapier/Make, or n8n.
You'd be a great fit with:
Industry Savvy: Strong background in manufacturing or organizations engaged in government contracting.
Modern Audit Toolkit: Hands-on experience with SQL, Python, DataSnipper or AI-based audit tools (e.g., Alteryx, MindBridge, or custom GPT agents).
Data: Proficiency in Data Governance, Datawarehouse (Snowflake/DataBricks)
AI technology is evolving everyday, critical requirements for this role are passion for AI, self learning, willingness to experiment and implement solutions that are pushing the boundaries.
Location: Remote, US
Travel: 10%
Job ID: 1389
The approximate base salary range for this position is $111,692 - $145,649. The total compensation package includes base, bonus, and equity.