Engagement: 2 weeks · 8 hours/week
Compensation: Competitive hourly rate
Location: Palo Alto, CA
About Us:
At Nace AI, we are redefining how professional services operate by delivering Sovereign Specialized Intelligence. As an applied research and product company, we equip enterprises with a comprehensive AI stack to build customized, secure intelligence tailored to their unique business needs.
Driven by advanced Small Language Models and our dynamic metamodel framework, our flagship platforms - Nace Data Intelligence and the Nace SLM Cloud - enable true end-to-end business process automation. The result is transformative ROI: professional services firms using Nace AI are currently recovering 1,000 hours per client engagement, drastically reducing overhead and accelerating delivery.
The work we are doing has a meaningful impact across industries, and every hire at Nace AI plays a critical role in shaping the company’s trajectory. This is a unique opportunity to join a high conviction AI company at an early stage and directly influence its growth.
If building a world-class AI team from the ground up excites you, we’d love to talk.
What you will actually do
Review AI-generated workpaper interpretations against real audit standards.
The system parses uploaded audit workpapers and makes decisions: which procedures address which assertions, what constitutes sufficient appropriate evidence, and where a potential misstatement exists. You will tell us when those decisions are audit-defensible and when they are not.
Define ground truth across account types and audit areas.
Revenue recognition, accounts receivable confirmations, inventory observations, debt covenants, management estimates, related-party disclosures — each behaves differently under AU-C standards. You will tell us what a correct result looks like for each, and provide real workpaper examples where possible.
Challenge the AI's risk and exception logic.
When the system identifies a transaction as potentially misstated, is it? When it concludes that substantive procedures are sufficient without further testing, 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.
Who this is for
You have 5+ years of hands-on financial audit experience, including direct workpaper preparation and review — not just oversight. You know what a peer reviewer or regulator looks for because you have been in that room.
You came up through a Big 4 or equivalent top-tier firm (EY, PwC, Deloitte, KPMG, or a national practice with equivalent audit depth). You hold a CPA and have worked across multiple clients and industry verticals, not just one sector.
You are intellectually curious about what AI gets wrong — not defensive about it. You see the potential for AI in audit and want to be part of getting it right from the beginning, before the standards catch up.
Minimum qualifications
5+ years of financial statement audit experience, hands-on
Big 4 or equivalent top-tier firm background required
Deep working knowledge of GAAS, AU-C standards, and PCAOB where applicable
CPA certification required
Experience spanning multiple audit areas and account types, not single-domain
Preferred
Experience leading audit engagements for mid-to-large cap public or private companies
Former senior associate or manager level — you reviewed others' workpapers
Exposure to audit analytics, data-driven testing, or audit technology platforms
Intellectual interest in where AI belongs — and doesn't belong — in regulated workflows