Guide

How to prepare an AI-evaluation hiring brief

Turn an AI-evaluation need into a brief that internal reviewers and a recruiting partner can act on. Start with the work to be assessed and the evidence needed to judge it.

The worksheet

QuestionWhat to provide
What decision will this work support?One sentence describing the decision or review outcome.
What is the task unit?A response, conversation, pull request, document, image or workflow run—and what the evaluator decides.
What context matters?Product surface, intended user, domain, language, version and constraints.
Who can judge it?Required practical experience, language fluency and domain knowledge. Separate essentials from trainable preferences.
What will good look like?A rubric with observable criteria, examples and a route for uncertainty.
How will acceptance work?Pilot scope, reviewer, cadence, disagreement handling and the final decision-maker.

Define the work before the role

“AI evaluator” can describe preference ranking, factuality review, code assessment, red-teaming, data-quality checks or a domain-specific rubric. Name the actual task. Specify the expected language, domain, product surface and schedule where known.

Bring a small evaluation package

Start with a small pilot, compare reviewers on the same sample and record what changed. The NIST AI Risk Management Framework can be a useful voluntary reference for structured questions about context and evaluation; this guide does not imply NIST conformance.

Next step

Use this worksheet to create a one-page brief, then compare the AI Talent Ops service or contact QuikHire to discuss the work.

Discuss a hiring brief