Lead your AI agent reviewer CV with decisions, not tasks. A reviewer is hired to approve, change or decline the work an agent holds, so the CV should show the kinds of cases you decide, the red lines you never cross, how accurate your decisions are, and a certificate an employer can check. A sample follows.
What is a reviewer CV for?
A reviewer CV answers one question for the hiring manager: will this person make the right call on the cases an agent cannot settle alone? Everything on the page should support that. If you are not sure what lands in a reviewer's queue, what an AI agent reviewer does explains it.
Many reviewers come straight from frontline work. Customer service staff, claims handlers, KYC analysts and AP clerks already decide cases under a policy every day. Your existing judgement is the asset; the CV shows it applies to agent work. Job titles differ: reviewer, case reviewer, decision analyst, operations specialist, human-in-the-loop analyst. Read the duties in the advert instead. If they mention approvals, exceptions, escalation, quality or "held items", it is review work.
How do you fill it in?
Three rules make the difference.
- Describe decisions, not activity. "Decided refund exceptions above the team limit" beats "handled customer queries".
- Name a red line. Say what you would always escalate or decline, such as a payment change resting on an emailed document. It shows you know where the risk sits.
- Show accuracy truthfully. If your work was quality-checked, say how it was checked and the standard you met. Do not invent figures. "Met the team quality standard every month" is fine if true.
Keep it to two pages. Put certificates near the top if they are current, because they are the quickest thing for an employer to verify.
The template
- Header: name, town, email, phone, profile link.
- Profile: Reviewer with [years] years deciding [case types] in [industry]. Holds [red line]. [Certificate] valid to [month and year].
- Certificates: [name], issued through [issuer], no. [number], valid to [month and year], checkable at source by number or QR code.
- Review experience: for each role: - Case types decided: [refunds, claims, onboarding files, invoices] - Your authority: [the limit you could approve to] - How decisions were checked: [sampling, calibration, second review] - One example: [a case you held, changed or escalated, and why]
- Other experience: earlier roles in one or two lines each.
- Skills: reading sources and their provenance, writing short decision reasons, escalation, calibration with colleagues, policy interpretation.
- Education and training.
- References: available on request.
A worked example
A sample only. Amira, an invented candidate, spent four years in onboarding at a regional bank.
Profile: Reviewer with four years deciding customer onboarding files in retail banking. Never approves an account where identity rests only on an uploaded document that has not been checked against a signed or sealed source. Certified Pryme Operator, valid for 12 months.
Review experience, onboarding analyst, a regional bank:
- Decided onboarding files the screening tool flagged: name matches, address mismatches, unusual sources of funds.
- Could approve standard-risk files; enhanced due diligence went to a senior analyst.
- Work sampled weekly by the quality team and calibrated monthly with three colleagues.
- Held a file where a utility bill matched the address but the account history did not; the customer had moved in that week and the senior analyst approved with an extra check.
Practicum: Two weeks of review decisions on a simulated onboarding queue, meeting the standard of nineteen in twenty correct with no missed red line, signed off by an assessor.
Skills: reading source documents and where they came from; writing a one-line reason for every decision; knowing when to escalate.
Amira's CV works because a hiring manager can picture her at the queue. Compare the AI quality reviewer CV template, which focuses on sampling decisions after the fact, and the AI operations manager CV template for the next step up. The AI agent jobs and careers guide covers the wider field, and how to become an AI agent reviewer covers the route in.
Questions people ask
Can I apply without ever reviewing an agent's work?
Yes. Frame your human decision-making as review experience, because that is what it is. A practicum on a simulated queue, such as the one in Pryme Intelligence Academy's Operator track, adds evidence of decisions on agent work specifically.
Should I list my quality scores?
List them only if they are real and you can explain how they were measured. A vague claim of high accuracy is weaker than a clear description of how your work was checked and the standard you met.
Is a red line on a CV too negative?
No. Reviewers are hired to stop the wrong things. One clear red line shows judgement and tells the reader you understand where the risk in the work sits.