How to write an honest AI job posting (and why candidates can tell when you don't)

If you hire for AI roles, you have probably noticed that the same title can mean three different jobs. Candidates have noticed too. A posting that says "AI Engineer" and describes a reporting dashboard loses the people you wanted, and attracts the people who want the title. This is a practical guide to writing a posting that tells the truth, with the market numbers it should be written against. Figures are from 16 October 2026.

Start from the market, not from the title

Level rates every live posting from 1 to 4 on how central AI is to the work. For the title "AI engineer", it found 650 live postings on 16 October 2026, and 599 of them were rated Level 3 or 4, which means the description makes AI a daily part of the work. Roughly 34% of those 650 postings were remote (218 of them). Only 179 of the 650 published a salary in USD, which is 28%, and among those the median posted minimum was $183,000.

Two things follow. First, if your "AI engineer" posting would be rated Level 1 or 2, it is an outlier against its own title, and candidates comparing postings will see it. Second, 72% of competing postings with this title do not publish a USD salary. Publishing a range sets yours apart.

The same page shows who else is hiring under that title: Capital One had 72 open roles, OpenAI 40, PwC 29, SpaceX 18 and Anthropic 15.

What a mismatch looks like

One example from the same day. A Senior AI Engineer (AI Factory) posting at Procter & Gamble in Warsaw named Vertex AI and Databricks and scored 25 out of 100, which is Level 1. That does not make it a bad role, and the score describes the text, not the team. It does show how a title with "AI" in it can sit next to a description that reads as something else. A candidate who wants model work will read the description, see little of it, and move on.

A six-part structure that scores honestly

1. One sentence on what the AI is. Is the person building a model, running an inference service, evaluating outputs, integrating a vendor API into a product, or using an assistant in their daily work? These are different levels (4, 3 and 2). Say which.
2. Name the tools and models. "PyTorch, vLLM and an internal evaluation harness" is information. "Cutting-edge AI technologies" is not. Specific names are a strong signal.
3. Describe a typical week in verbs. Build, train, evaluate, deploy, monitor, review, sell, support. If three of the five verbs are about AI work, say so. If one is, say that.
4. Separate must-haves from nice-to-haves. Candidates read a long list as a hard requirement. If fine-tuning is a plus, mark it as one.
5. State the pay range and the location rules. A range, the currency, and the exact remote policy ("remote within the US", not "flexible").
6. Say what the role is not. "You will not be training foundation models" saves both sides a week.

Check it before you publish

Paste the draft into the AI Level Checker on the Level site. It is a rules-based check that looks for AI tools and skills in the text, it runs in memory, and nothing you paste is stored. Its result can differ by one level from a listing that a model has also reviewed, so treat it as a first read. The useful question is whether the result matches what you meant. If you intended Level 3 and the checker says Level 1, the posting is hiding the work.

Common ways honest postings go wrong

• Scenery mentions. A company tagline about AI at the top of the page, followed by duties that do not involve it. The scale treats this as Level 1 by definition.
• One-bullet AI. A single line out of fifteen that mentions a model. That is a Level 2 job at best.
• Title inflation. Using "AI" to describe an ordinary analyst or sales role in order to widen the funnel. It widens it with the wrong people.
• Silence. A role that really involves AI but never says how. A badly written description can understate a role, and the level will reflect that.

Why bother

A rated posting lets the candidate know the depth of AI work before they apply, which means fewer mismatched applications and fewer first-call surprises for your team. None of this requires hiding a weaker role. A Level 2 role described accurately attracts people who want a Level 2 role.

Method

• Data: the AI engineer title scope on Level, 650 live postings, 179 with a published USD salary, read on 16 October 2026. No currency conversion.
• Example: one Procter & Gamble posting, retrieved with Level's search tool on 16 October 2026.
• Limits: postings on other job boards for the same title are not counted.

Level's own breakdown is published in its guide to hiring an AI engineer.