IonQ

Staff Automation Engineer - Internal Audit

IonQ$111K — $145K *
US-AnywhereRemote in United States
Business Services
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's degree in Industrial Engineering, Information Systems, Data Science, or Accounting with a technical focus
  • 5-8+ years in Audit Transformation, Process Excellence, or Business Systems Engineering
  • Hands-on experience with LLM orchestration (Vellum, LangChain, or Copilot Studio)
  • Advanced proficiency in Power Automate, Zapier/Make, or n8n
  • Proficiency in Data Governance and Data Warehouse technologies such as Snowflake or DataBricks

Responsibilities

  • Analyze and map end-to-end audit processes to identify automation opportunities
  • Apply Lean/Six Sigma principles to streamline the audit lifecycle
  • Design reusable workflow patterns across Financial, IT, and Operational audits
  • Build and deploy AI-supported workflows using tools like Vellum AI and Copilot Studio
  • Develop a library for prompts and agents to standardize AI interactions
  • Create automated workflows that reason through exceptions and update GRC platforms
  • Maintain real-time risk visualizations in Power BI or Tableau based on automated results

Benefits

  • Comprehensive medical, dental, and vision plans
  • Matching 401(k)
  • Unlimited PTO and paid holidays
  • Parental/adoption leave
  • Legal insurance
  • Home technology stipend
Full Job Description
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: 1. Audit Architecture & Process Re-Engineering • 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. 2. AI Agent Orchestration & Prompt Engineering • 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. 3. Automation & Ecosystem Integration • 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. 4. Governance, Privacy & "Auditability" • 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, DataSnipperor 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: 1675 The approximate base salary range for this position is $111,692 - $145,649. The total compensation package includes base, bonus, and equity. Compensation will vary based on individual factors such as education, qualifications, and experience of the final candidate(s), specific office location, and calibration against relevant market data and internal team equity. Posted base salary figures are subject to change as new market data becomes available. Our benefits include comprehensive medical, dental, and vision plans, matching 401(k), unlimited PTO and paid holidays, parental/adoption leave, legal insurance, and a home technology stipend. Details of participation in these benefit plans will be provided when a candidate receives an offer of employment.

About IonQ

IonQ is a quantum computing company that is developing a general-purpose, full-stack quantum computer based on trapped ion technology. The company was founded in 2015 by Chris Monroe and Jungsang Kim. IonQ's quantum computer is designed to be scalable, error-corrected, and fault-tolerant, and is expected to be able to solve problems that are intractable for classical computers. The company has partnerships with Microsoft, Amazon Web Services, and others. IonQ has raised over $225 million in funding to date.
Learn more about IonQ
Size
100 employees
Market Cap
$633 million
Industry
Founded
2016
NASDAQ

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