GEO and AEO for Careers Websites: The Complete Guide (2027)

GEO and AEO for careers websites come down to one idea: make it easy for a search engine or an AI assistant to understand who you are, what you offer and which jobs are open, then make that information accurate, consistent and worth quoting. Google says the best SEO practices still apply to AI search. The research says some writing choices help AI tools cite you more. And the 15 careers websites we checked show what the basics look like in practice.

This guide is the hub for our work on AI visibility. It builds on our ultimate SEO guide for careers websites and our guide to GEO vs SEO for careers content, links to the deeper technical write ups, and adds expert opinion with references and evidence from our own tests. You may see the same topic called GEO for careers sites, AEO for careers sites or AI search for careers sites. It is the same job: being the source an answer engine trusts.

• Key takeaways
• What GEO and AEO mean
• What the experts say
• The technical foundations
• Seven techniques that help
• Evidence from our own work
• Making it easier
• The checklist
• FAQ
• Related reading
• Sources

What GEO and AEO mean for a careers website

GEO, generative engine optimisation, is the practice of shaping your content so generative AI tools, such as ChatGPT, Perplexity, Gemini and Google’s AI Overviews, can find it, trust it and cite it when someone asks about your company or your jobs. AEO, answer engine optimisation, is the older sibling: structuring pages so a search engine can lift a short, direct answer, as in featured snippets, voice answers and AI summaries. For a careers website the two overlap almost completely, so we treat them together.

The audience has changed fast. Richard Mosley, managing partner at C-YourCulture, says “up to 70% of candidates now appear to be using these platforms” to size up employers. Whatever the exact figure, the direction is clear: a candidate may meet your employer brand inside an AI answer before they ever reach your careers website.

Three questions sit behind every tactic in this guide. Can the machine read the page? Can it tell what the page is about and trust it? And is the answer on the page worth quoting? The sections below take each in turn. For the classic ranking side, see our SEO guide for careers websites; for the short comparison, see SEO vs AEO vs GEO. If you only want to know how GEO differs from SEO, our GEO vs SEO in 2026: how to make your careers website visible to AI is the quicker read, and this guide goes deeper on the practice.

What the experts say

We looked for named people and primary sources, and quote them exactly. Where experts agree, we say so. Where they differ, we say that too.

Google: the basics still apply

“The best practices for SEO remain relevant for AI features in Google Search (such as AI Overviews and AI Mode). There are no additional requirements to appear in AI Overviews or AI Mode, nor other special optimizations necessary.”

Google Search Central, guidance on AI features and your website. Read the guidance

The same page advises allowing crawling, linking internally, offering a good page experience, supporting text with quality images and video, and “making sure your structured data matches the visible text on the page”. It adds that you do not need new machine readable files, AI text files or special schema.org markup to appear in these features. In short: do the fundamentals well.

Richard Mosley: write for the human and the machine

Richard Mosley co-authored The Employer Brand, which its publisher describes as the first book on the subject, spent ten years at Universum, wrote Employer Brand Management and co-wrote Employer Branding for Dummies. He leads C-YourCulture as managing partner and is one of the people we feature in our list of employer branding experts to follow in 2027. In a July 2026 interview with Intelligence Group he made three points that translate directly into careers website practice.

“It’s much more about making sure your messages get across in a way that’s readable and citable by the LLMs”

Richard Mosley, managing partner, C-YourCulture. Intelligence Group, 29 July 2026

“The LLMs can get a bit confused if you’ve got lots of different and sometimes conflicting messages about what you truly stand for”

Richard Mosley, managing partner, C-YourCulture. Intelligence Group, 29 July 2026

His distinction between audiences is a useful brief for any careers website team: the human reader is moved by feel, stories and intuition, while the machine audience is, in his words, “super rational”. Your pages need both: stories for people, and clear, consistent, factual statements for the machine to quote.

John Mueller: llms.txt is not the lever

“FWIW no AI system currently uses llms.txt.”

John Mueller, Search Advocate, Google. Bluesky post of 17 June 2025, reported by Search Engine Roundtable

He added that the consumer chatbots fetch your pages for training and grounding but “none of them fetch the llms.txt file”. An Ahrefs study of 137,000 sites reached a similar conclusion in its headline: 97% of llms.txt files never get read. That is a view as of those dates, and it could change, so we cover llms.txt honestly in the technical section.

Rand Fishkin: measure many answers, not one

Rand Fishkin, co-founder and CEO of SparkToro and co-founder of Moz, worked with Gumshoe’s Patrick O’Donnell on a January 2026 study. 600 volunteers ran 12 prompts through ChatGPT, Claude and Google’s AI a combined 2,961 times. The lesson for anyone checking how AI describes their company is that one answer proves nothing.

“If you ask an AI tool for brand/product recommendations a hundred times nearly every response will be unique”

Rand Fishkin, co-founder and CEO, SparkToro. SparkToro, 27 January 2026

In that study the chance of two responses giving the same list of brands was under 1 in 100, and the chance of the same order was closer to 1 in 1,000. The study looked at product and brand recommendation prompts rather than employer brand questions, so treat it as a method lesson: sample widely and look at patterns.

The GEO research: what actually moved visibility

The term itself comes from academic research. A team including researchers at Princeton University and IIT Delhi proposed generative engine optimisation in 2023 and published it at the KDD 2024 conference. Across their benchmark, the best methods boosted visibility in generative answers by up to 40%. Citing sources, adding quotations and adding statistics were the strongest, at roughly 30 to 40% on one measure; fluent, well-edited writing also helped. Keyword stuffing gave little to no improvement, and the gains reached up to 37% on Perplexity.ai.

Two cautions keep this honest. The benchmark used general questions rather than careers queries, and AI products change constantly. The practical reading is still sound: pages that quote credible sources, state facts precisely and read well are easier for a generative tool to use.

Want more voices? Our list of employer branding experts to follow in 2027 celebrates the people shaping this field.

The technical foundations

These are the checks we ran on 15 live careers websites. Each one is a practice anyone can verify in a few minutes with view source, a robots.txt file and a sitemap.

Structured data: Organization, WebSite and JobPosting

Structured data is a labelled summary of the page for machines. Three types matter for a careers website. Organization tells search tools who you are, with your name, logo and official profiles. WebSite (with SearchAction) describes your site and its search. JobPosting describes each vacancy: the title, description, location, employment type, date posted and who is hiring. Google uses JobPosting to show jobs in Google for Jobs, and it gives any other system clean facts to work from.

The rule that matters most is Google’s: the markup must match the visible text. In our check, 12 of 15 home pages carry Organization markup, 2 also carry WebSite with SearchAction, and 14 of 15 live job pages carry JobPosting markup in the page source (the remaining one adds it once the page renders). Every one of those 14 job pages includes the core fields below.

The next layer is optional but valuable: validThrough (when a vacancy has a real closing date), baseSalary, directApply and, for remote roles, applicantLocationRequirements and jobLocationType. Each of these appeared on a few of the pages we checked, which makes them a clear next step for any careers website team. Here is a minimal example with placeholder values:

{
  "@context": "https://schema.org",
  "@type": "JobPosting",
  "title": "Senior Software Engineer",
  "description": "<p>The same text a candidate sees on the page.</p>",
  "datePosted": "2026-10-01",
  "validThrough": "2026-12-01T23:59",
  "employmentType": "FULL_TIME",
  "identifier": { "@type": "PropertyValue", "name": "Example Co", "value": "R-12345" },
  "hiringOrganization": { "@type": "Organization", "name": "Example Co", "sameAs": "https://www.example.com" },
  "jobLocation": { "@type": "Place", "address": { "@type": "PostalAddress",
    "addressLocality": "London", "addressCountry": "GB" } },
  "directApply": true
}

For the full field by field walkthrough, including salary, remote work and common errors, see our guide to JobPosting schema for careers websites.

Crawlability: let the right bots in

If a crawler cannot fetch your pages, nothing else matters. OpenAI documents separate robots.txt controls for separate jobs: OAI-SearchBot is for search and “is used to surface websites in search results in ChatGPT’s search features”, GPTBot is for training, and ChatGPT-User visits pages when a user asks. OpenAI notes that each setting is independent, and recommends allowing OAI-SearchBot if you want to appear in ChatGPT search.

That separation is a gift to employers, because you can decide about training and visibility separately. Across the 15 careers websites we checked, none blocks OAI-SearchBot, ChatGPT-User, Claude-User, PerplexityBot, Google-Extended or Applebot-Extended, none uses a blanket Disallow of the whole site, and 14 list their sitemap in robots.txt. Several choose to opt out of training-only crawlers while staying open to search and citation, which is exactly the split the documentation describes.

Job sitemaps with lastmod dates

A sitemap tells crawlers which URLs exist; a lastmod date tells them which have changed. For a careers website, where jobs open and close daily, that is the signal that keeps answers fresh. 14 of the 15 careers websites we checked publish job sitemaps where every job URL carries a lastmod date, adding up to more than 42,000 job URLs.

Server-rendered content

AI crawlers and search crawlers vary in how much JavaScript they run, so the safest careers website puts the important facts in the HTML itself. The job pages we checked contain between 528 and 2,520 words in the raw HTML, including the job description, location and apply details. That is the standard to aim for: if a page is useful with scripts switched off, any crawler can read it.

llms.txt: what we know

llms.txt is a proposed plain text file that lists a site’s key pages for AI tools. None of the 15 careers websites we checked has one, and the evidence above suggests that is a reasonable position today: Google’s documentation says you do not need AI text files to appear in its AI features, Mueller says no AI system currently uses the file, and Ahrefs found most files never get requested. If you want to add one, it is harmless; just do it after the work that is proven to matter.

Structured, answer-first content

This is the part you control most. Put the direct answer first, in plain language, then the detail: what the role is, where it is, what the pay and benefits are, what the application steps are. Use one clear H1 per page, descriptive H2s, short paragraphs and a visible FAQ for the questions candidates really ask. Then make sure any FAQ markup matches the visible questions word for word, as Google requires.

Conversational search takes this one step further: a candidate asks a question in their own words and the careers website answers from its own FAQs, policy pages and employer brand content. Our guide to the conversational careers website shows how.

Seven techniques that help

Each technique is tied to a source, so you can judge the strength of the evidence yourself.

1. Say the same thing everywhere. Align your careers website, LinkedIn page, job descriptions and press copy on what you stand for. Richard Mosley warns that conflicting messages confuse AI tools.
2. Cite your sources. When you state a fact about benefits, pay, awards or research, link to where it comes from. Citing sources was among the strongest methods in the GEO research.
3. Quote real people. Employee quotes, named and attributed, add the kind of quotation signal the research found helpful, and they are the human half of Mosley’s two audiences.
4. Use specific numbers. Salary ranges, team sizes, years of tenure and programme dates are statistics a generative tool can quote accurately.
5. Write answer-first FAQs. Mirror the questions candidates ask, answer in the first sentence and keep markup identical to the visible text.
6. Keep jobs fresh. Accurate lastmod dates, validThrough and removal of closed jobs keep AI answers and Google for Jobs from showing stale vacancies.
7. Test with repeated prompts. Ask the same question 60 to 100 times, as the SparkToro study did, across several tools, and track how often your employer is mentioned and how it is described.

What does not appear to help: stuffing keywords. The GEO research found little to no improvement from it, which matches Google’s long-standing advice to write for people.

Evidence from our own work

We checked the page source, robots.txt, sitemaps and a live job page for each of the 15 careers websites in our best careers sites of 2026 ranking, all built on Happydance. Tests ran on 31 October 2026. The charts above show the results in aggregate. Here is what several of these careers websites do well, each verifiable on the live site.

• Coupa

  Its job page carries the richest JobPosting markup we found, including salary and remote location fields, plus Organization markup with a logo and official profile links on the home page.

  See the live careers website

• Johnson and Johnson

  A job sitemap of 23,119 URLs, every one with a lastmod date, JobPosting with a validThrough date, and 16 hreflang language and region links on the home page.

  See the live careers website

• Veterans United

  Home page markup for Organization, WebSite with SearchAction and contact details, and JobPosting that includes a validThrough date on its job pages.

  See the live careers website

• Dropbox

  JobPosting markup that includes remote work fields, so the nature of a role is machine readable, alongside Organization markup with official profile links.

  See the live careers website

• Intuitive

  A job sitemap of 5,060 URLs with lastmod dates and six hreflang language and region links, built to scale across a global job feed.

  See the live careers website

• Wells Fargo

  WebSite markup with SearchAction on the home page, a job sitemap of 4,705 URLs with lastmod dates and hreflang language links on the home page.

  See the live careers website

A real result: Coupa and ChatGPT

Visibility in AI search only matters if it brings candidates. When Coupa launched its new careers website in May 2026, it picked up 212 sessions arriving via ChatGPT in month one, up from 161 across the entire previous two months, converting at 20.59%. That is from our own write up, Technology doesn’t create authenticity, it has to carry it, and it is the kind of number you can only see if you track AI referrals separately in analytics.

A note on method: this check covers technical readiness, not rankings or how any AI tool describes an employer, because AI answers vary from run to run. We have not published per-site crawler settings, and every figure here can be reproduced from public pages.

Making it easier: where Happydance helps

Every practice above takes effort to do by hand and to keep right across thousands of jobs. These are the Happydance features that take the load, each one described on the Happydance site.

Learn more about the AI careers website platform, Conversational Navigation, the analytics dashboard and the SEO Concierge Service.

The GEO and AEO checklist for a careers website

Work down this list in order. The first six are technical; the last six are content.

1. Confirm robots.txt allows search and citation crawlers, and list your sitemap in it.
2. Publish a job sitemap with an accurate lastmod date on every URL, and remove closed jobs.
3. Add JobPosting markup to every job page with the core fields and, where they apply, validThrough (for a real closing date), salary and remote fields.
4. Add Organization (and WebSite) markup to the home page with your logo and official profiles.
5. Check that the key facts are in the raw HTML, with one H1, descriptive H2s and a canonical link.
6. Make sure any structured data matches the visible text on the page.
7. Agree one clear statement of what you stand for and use it consistently.
8. Add named employee quotes and specific numbers to key pages, and link to sources.
9. Add an answer-first FAQ to the careers website home page and your top job families.
10. Skip keyword stuffing; edit for fluency and clarity.
11. Test how AI tools describe you with 60 to 100 repeated prompts and record the pattern.
12. Track AI referrals in analytics and review monthly.

Want a second pair of eyes? The careers website audit and the AI visibility audit review these areas for your own careers website, and our careers website audit checklist lets you score it yourself.

GEO and AEO for careers websites: frequently asked questions

Related reading

Sources

• Google Search Central, AI features and your website: developers.google.com/search/docs/appearance/ai-features
• John Mueller, Bluesky, 17 June 2025, reported by Search Engine Roundtable: seroundtable.com/google-ai-llms-txt-39607.html
• Ahrefs, We Analyzed 137K Sites: 97% of llms.txt Files Never Get Read: ahrefs.com/blog/llmstxt-study
• OpenAI, Overview of OpenAI crawlers: platform.openai.com/docs/bots
• Richard Mosley interview, Intelligence Group, 29 July 2026: intelligence-group.nl/resources/up-to-70-of-candidates-now-size-you-up-via-ai-too-
• Rand Fishkin, SparkToro, AIs are highly inconsistent when recommending brands or products, 27 January 2026: sparktoro.com/blog/new-research-ais-are-highly-inconsistent-when-recommending-brands-or-products-marketers-should-take-care-when-tracking-ai-visibility
• Aggarwal et al., GEO: Generative Engine Optimization, KDD 2024: arxiv.org/abs/2311.09735
• Google Search Central, JobPosting structured data: developers.google.com/search/docs/appearance/structured-data/job-posting
• Happydance, Technology doesn’t create authenticity, it has to carry it (Coupa): https://www.happydance.love/insights/posts/technology-doesnt-create-authenticity-it-has-to-carry-it/
• Happydance check of 15 careers websites: page source, robots.txt, sitemaps and one live job page each, 31 October 2026.