Audit Methodology Lead

We build AI agents that perform audit procedures for audit firms. We need an experienced auditor to decide what correct output from those agents looks like, and whether our agents meet that bar.

You'll join one of our product groups as its audit expert. You'll write the criteria and reference cases our agents are tested against, review agent output the way you'd review a file, and tell the team plainly when something isn't ready for a live engagement. You'll use AI to create realistic test material, and you'll review all of it yourself.

The hardest AI problems aren't about getting an answer fast. They're about getting one people can trust.

We believe trust is essential to how society works. Every day, we rely on information that's been independently verified, from financial statements to the products we buy, to the sustainability claims companies make. Behind that trust are audit and finance professionals who examine evidence, verify information and hold organizations accountable.

At DataSnipper, we build AI solutions that empower those professionals. By making evidence easier to trace and verify, we help them focus on the judgment and expertise that make their work so important.

For our product and engineering team, this is where things get exciting. In audit, a plausible answer isn't good enough. Every output has to be explainable and traceable back to its source. We've just launched a brand new agentic platform, Alwin by DataSnipper. AI agents running in the cloud across hundreds of documents at once, reasoning across PDF, Word and Excel, with a full audit trail behind every step. There are lots of greenfield problems ahead, and real room to shape what we build and how we build it.

And we build at scale. More than 600,000 professionals across 3,000+ organizations in 175 countries rely on DataSnipper, including Fortune 500 companies, government agencies and all Big Four audit firms. In 2025 alone, the DataSnipper platform delivered more than $1.4 billion in productivity savings to is customers. Backed by a $100 million Series B led by Index Ventures, at a $1 billion valuation, and as proud members of 1% for the Planet, we care about how we grow, not just how fast.

If you want to build AI that professionals trust with work that really matters, this is your chance to help shape the future of audit and finance and do the best work of your career along the way.

• Define the correct answer, and the reasoning behind it, for the procedures our agents perform

• Interpret ISAs and NV COS (IFRS for reporting matters; US GAAS and PCAOB where relevant) into requirements engineers can build against

• Create realistic audit cases with AI tools, including documents, workpapers, exceptions and judgement calls, and review every one

• Review agent output against those cases, and find misapplied standards, weak reasoning and conclusions that wouldn't pass partner review

• Turn recurring errors into findings product and engineering can fix

• Give a clear, evidenced view on whether a capability is ready for live engagements

• Review methodology content from partners and our own teams, with versioning, approval and documented changes

• Track changes in standards and inspection findings, and explain what they mean for the product

• Teach product and engineering how audit work is actually done, including how firms differ

• Work with customers and content partners when the work requires it

• A professional qualification: RA, AA, CPA, CA, ACA, ACCA or equivalent

• Experience as an Audit Manager: setting the approach, reviewing others' work, clearing review notes and defending conclusions

• Recent experience across several clients and industries

• Working knowledge of ISQM 1 and how firms document and review audit work

• Regular use of AI tools, and a clear sense of how they fail

• Precise writing: people without your training will build from what you write

• Patience for detail: line-by-line review, and real time spent on a single conclusion

Nice to have:

• You want to use your audit expertise on hard problems in AI: judgement, evidence and review

• You'd rather change how audit work is done than automate how it's done today

• You've built something yourself, such as a tool, prototype or workflow, to fix a slow process

• You stay with open-ended problems until the answer holds up

• Not product management. You shape what ships, but you don't own the roadmap

• Not implementation or customer success

• Not volume work. AI produces the volume; you decide what's right

• Recruiter screen

• Interview with an Audit Expert

• Assessment interview

• Final conversations with the people you would work alongside

At DataSnipper, we believe great ideas come from different perspectives, experiences, and backgrounds. We are committed to building an inclusive workplace and providing every candidate with a fair and equitable hiring experience.

Our hiring decisions are merit-based and grounded in the skills, experience, potential, and capabilities relevant to the role.

We welcome applicants regardless of age, race, ethnicity, nationality, gender, gender identity or expression, sexual orientation, religion, disability, or any other characteristic that makes you, you.

What matters to us is what you can bring to the role, the team, and DataSnipper. 🚀