AI Trainer – Accounting

is looking for experienced accounting professionals to evaluate how frontier AI models handle real accounting work: technical accounting conclusions, close and reconciliation, audit procedures, tax positions and provisions, and financial reporting. You bring the judgment you have built clearing review notes, tying out work papers and defending positions to auditors, partners or the audit committee. We bring the model output that judgment is needed to grade.

In this role, you will design challenging, realistic tasks drawn from your own practice, such as a month end close reconciliation package, a technical accounting memo on a revenue or lease question, a tax provision workpaper, an audit sampling plan and results, a disclosure checklist, or a management letter comment, run them through frontier AI agents, and evaluate what comes back against a professional standard.

You will work with realistic professional files, the kind a practitioner in your field actually handles, which you assemble yourself. Some tasks are compact, built around a handful of files; others are larger scenarios that take several days to build. In every case the goal is the same: a task a competent professional in your field would complete correctly and a frontier model currently gets wrong.

This is not a traditional accounting role. You will be helping build better AI by putting your knowledge to work in a structured, flexible, fully remote environment. The work is long form and self directed, and clear written reasoning matters as much as technical depth.

• Design challenging, realistic accounting tasks drawn from your own day to day work: the scenario, a prompt phrased the way you would brief a trusted colleague, and the supporting files a professional would need (trial balances, schedules, source documents, prior year work papers, correspondence), which you author yourself.
• Run those tasks through frontier AI models and evaluate the deliverable they produce (the workpaper, memo, schedule or reconciliation) against the standard you would hold a colleague to.
• Compare two model outputs on identical prompts and files, decide which performed better, and document where each fell short.
• Write detailed grading rubrics that specify what a correct deliverable must contain, such as the right treatment applied, the right amounts, the right disclosures and the right support, and explain in writing why a response passes or fails each one.
• Flag concrete failures with evidence: misapplied standards, numbers that do not tie, unsupported conclusions, fabricated or ignored source documents, missed disclosures, and off brief interpretation of the ask.
• Contribute across audit, technical accounting, tax, close and reporting, and review and refine tasks built by other experts.

• 2+ years of hands on experience preferred in public accounting, corporate accounting, audit, tax, or financial reporting.
• In progress Bachelor’s degree or higher in accounting, finance or a related field.
• Depth in at least one of: audit and assurance; technical accounting and financial reporting (US GAAP and/or IFRS); tax (individual, corporate, partnership, provision); controllership, close and consolidation; cost and managerial accounting; internal audit and SOX; forensic accounting.
• Working understanding of several of the others, enough to know what those workflows involve and how they are run, so you can assess work in an adjacent area and point out what was done correctly or incorrectly.
• Comfortable in spreadsheets at a practitioner level: building and checking schedules, reconciliations and roll forwards, not only reading them.
• CPA, CA, ACCA or equivalent is preferred but not required. Practical expertise outweighs credentials. Credential holders may be asked to verify the credential during the assessment.

• 2+ years of hands on experience in your field preferred (see Domain qualifications above). Candidates with less experience are considered where the practical work is real.
• Able to draw on your own real world experience and day to day workflows to craft scenarios that test whether an AI system can actually do the work.
• Hands on practitioner: you currently do (or recently did) the work yourself at an individual contributor level, not solely in a managerial capacity.
• Full professional or native level written and spoken English, with strong written communication. You can explain complex professional reasoning clearly and concisely, and…