SOX Audit Expert

Nace AIPalo Alto, CA

About The Position

We are building an AI-native platform for SOX control testing — one where an AI agent reads an audit workpaper, classifies every sheet, extracts sample rows, identifies exceptions, and generates PCAOB-defensible narratives. Automatically. The engineering is working. What it needs now is an expert who can tell us when it's right and when it only looks right. This is not a training role. This is not a data labeling role. This is the role where a seasoned auditor looks at what the AI produced, applies the kind of judgment that comes from years of real engagements, and tells us exactly where professional standards would push back — and why. Your input directly shapes how AI handles SOX compliance for public companies. That influence starts on day one.

Requirements

  • 5+ years of hands-on SOX audit experience, including direct workpaper preparation and review — not just oversight.
  • Know what a PCAOB reviewer looks for because you have been in that room.
  • Came up through a Big 4 or equivalent top-tier firm (EY, PwC, Deloitte, KPMG, or a national practice with equivalent SOX depth).
  • Hold a CPA and have worked across multiple clients and control environments, not just one industry.
  • Intellectually curious about what AI gets wrong — not defensive about it.
  • See the potential for AI in audit and want to be part of getting it right from the beginning, before the standards catch up.
  • 5+ years SOX compliance and financial audit experience, hands-on Big 4 or equivalent top-tier firm background required
  • Deep working knowledge of PCAOB standards and COSO framework
  • CPA certification required
  • Experience spanning multiple control types, not single-domain

Nice To Haves

  • Experience leading SOX workstreams for mid-to-large cap public companies
  • Former senior associate or manager level — you reviewed others' workpapers
  • Exposure to control testing automation or GRC tools
  • Intellectual interest in where AI belongs — and doesn't belong — in regulated workflows

Responsibilities

  • Review AI-generated workpaper interpretations against real audit standards. The system parses uploaded Excel workpapers and makes decisions: which tab is the testing table, which rows are samples, which variance is an exception. You will tell us when those decisions are audit-defensible and when they are not.
  • Define ground truth across control types. Reconciliation controls, management review controls, IT access reviews, three-way match, segregation of duties — each behaves differently. You will tell us what a correct result looks like for each, and provide real workpaper examples where possible.
  • Challenge the AI's exception logic. When the system flags a variance as an exception, is it? When it concludes a control is effective with limited samples tested, should it? You provide the professional judgment the engineering team cannot.
  • Shape the product roadmap. You will identify gaps between what auditors actually need and what the system currently produces. Those gaps become the next build cycle.
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