Technical22 February 2026·20 min read

Structured Data for Employer Brands: A Technical Guide to JSON-LD

Structured data is the only format AI models reliably treat as authoritative when answering questions about your company.

It's not marketing copy. It's machine-readable facts in a standardized format that Google, ChatGPT, Claude, and Perplexity all parse and trust.

This is a complete, technical implementation guide for developers and technical SEOs. By the end, you'll have working JSON-LD markup for your entire employer website.

What is JSON-LD and Why It Matters
Schema.org Vocabulary for Employers
Implementation: Step-by-Step
Organization Schema (Homepage)
JobPosting Schema (Job Listings)
FAQPage Schema (Careers Page)
EmployerAggregateRating Schema
BreadcrumbList Schema
Validation & Testing
Common Mistakes
Maintenance & Updates

1. What is JSON-LD and Why It Matters

What is JSON-LD?

JSON-LD (JavaScript Object Notation for Linked Data) is a format for embedding structured data in HTML.

It looks like this:

<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "Organization",
  "name": "Acme Corp",
  "url": "https://acmecorp.com"
}
</script>

You add it to your <head> or <body> tag, and search engines + AI models parse it to understand your page content.

Why JSON-LD vs. Microdata or RDFa?

Three ways to add structured data:

Microdata (inline HTML attributes)
RDFa (inline HTML attributes)
JSON-LD (separate JSON block)

JSON-LD wins because:

Easier to implement (no need to modify existing HTML)
Easier to maintain (all schema in one block)
Google's preferred format (official recommendation)
AI-friendly (models parse JSON natively)

Why It Matters for Employer Brands

Research from Profound analyzing 680M AI citations found:

32% higher citation rate for domains with schema.org markup
40% better factual accuracy in AI responses
2.8x more likely to be cited as a source by Perplexity
Immediate impact (works as soon as Google/AI crawlers re-index your site)

Translation: If you implement structured data correctly, AI models will cite your facts instead of guessing.

2. Schema.org Vocabulary for Employers

Schema.org defines 800+ types of things you can describe. For employer branding, you need these 5 core schemas:

Schema Type	Where to Use	What It Describes	Impact
Organization	Homepage	Company basics (name, location, size)	High
JobPosting	Job listing pages	Open roles with salary data	High
FAQPage	Careers page	Common candidate questions	Medium
EmployerAggregateRating	Careers page	Review data (if you have it)	Medium
BreadcrumbList	All pages	Navigation hierarchy	Low

Let's implement each.

3. Implementation: Step-by-Step

Option 1: Direct HTML Injection

Add <script type="application/ld+json"> blocks to your HTML:

<!DOCTYPE html>
<html>
<head>
  <title>Acme Corp</title>
  <script type="application/ld+json">
  {
    "@context": "https://schema.org",
    "@type": "Organization",
    "name": "Acme Corp"
  }
  </script>
</head>
<body>
  <!-- Your content -->
</body>
</html>

Pros: Simple, works everywhere
Cons: Hard to maintain if you have many pages

Option 2: React/Next.js Component

If you're using React or Next.js:

// components/StructuredData.tsx
interface OrganizationSchemaProps {
  name: string;
  url: string;
  description?: string;
}

export function OrganizationSchema({ name, url, description }: OrganizationSchemaProps) {
  const schema = {
    "@context": "https://schema.org",
    "@type": "Organization",
    name,
    url,
    description,
  };

  return (
    <script
      type="application/ld+json"
      dangerouslySetInnerHTML={{ __html: JSON.stringify(schema) }}
    />
  );
}

Use in your page:

// app/page.tsx
import { OrganizationSchema } from "@/components/StructuredData";

export default function HomePage() {
  return (
    <>
      <OrganizationSchema
        name="Acme Corp"
        url="https://acmecorp.com"
        description="Fintech building payment infrastructure"
      />
      {/* Your page content */}
    </>
  );
}

Pros: Reusable, type-safe, maintainable
Cons: Requires React/Next.js

Option 3: Server-Side Injection (PHP/Laravel/Rails)

Generate JSON-LD on the server:

// In your PHP view
<?php
$schema = [
  '@context' => 'https://schema.org',
  '@type' => 'Organization',
  'name' => 'Acme Corp',
  'url' => 'https://acmecorp.com'
];
?>

<script type="application/ld+json">
<?= json_encode($schema, JSON_UNESCAPED_SLASHES | JSON_PRETTY_PRINT) ?>
</script>

Pros: Works with any backend
Cons: Requires server logic

Option 4: CMS Plugins

WordPress:

Webflow:

Add via custom code blocks in Page Settings

Shopify:

Built-in for products, but you'll need to add Organization schema manually

4. Organization Schema (Homepage)

This is your highest-priority implementation. Add it to your homepage.

Minimum Viable Schema

{
  "@context": "https://schema.org",
  "@type": "Organization",
  "name": "Acme Corp",
  "url": "https://acmecorp.com",
  "logo": "https://acmecorp.com/logo.png"
}

Impact: AI now knows your name, website, and logo.

Full Schema (Recommended)

{
  "@context": "https://schema.org",
  "@type": "Organization",
  "name": "Acme Corp",
  "legalName": "Acme Corporation Ltd",
  "url": "https://acmecorp.com",
  "logo": "https://acmecorp.com/logo.png",
  "description": "We build payment infrastructure for modern commerce. 250 people, 15 countries, $500M+ processed annually.",
  "foundingDate": "2015-03-15",
  "numberOfEmployees": {
    "@type": "QuantitativeValue",
    "value": 250
  },
  "address": {
    "@type": "PostalAddress",
    "streetAddress": "123 Tech Street",
    "addressLocality": "London",
    "addressRegion": "England",
    "postalCode": "EC1A 1BB",
    "addressCountry": "GB"
  },
  "contactPoint": {
    "@type": "ContactPoint",
    "contactType": "HR",
    "email": "careers@acmecorp.com",
    "telephone": "+44-20-1234-5678"
  },
  "sameAs": [
    "https://www.linkedin.com/company/acmecorp",
    "https://twitter.com/acmecorp",
    "https://www.glassdoor.com/Overview/Working-at-Acme-Corp",
    "https://github.com/acmecorp"
  ]
}

Field Explanations

Field	Required?	Purpose
`@context`	✅ Yes	Tells parsers this is schema.org data
`@type`	✅ Yes	What type of thing this is (Organization)
`name`	✅ Yes	Your company name
`url`	✅ Yes	Your homepage URL
`logo`	✅ Yes	Square logo PNG (min 112×112px)
`description`	⚠️ Recommended	One-sentence description (AI uses this heavily)
`foundingDate`	⚠️ Recommended	When you were founded (ISO 8601 date)
`numberOfEmployees`	⚠️ Recommended	Employee count (can be approximate)
`address`	⚠️ Recommended	Headquarters address
`contactPoint`	Optional	HR contact info
`sameAs`	⚠️ Recommended	Links to your profiles on other platforms

For Multi-Location Companies

If you have multiple offices:

{
  "@context": "https://schema.org",
  "@type": "Organization",
  "name": "Acme Corp",
  "url": "https://acmecorp.com",
  "logo": "https://acmecorp.com/logo.png",
  "address": [
    {
      "@type": "PostalAddress",
      "addressLocality": "London",
      "addressCountry": "GB"
    },
    {
      "@type": "PostalAddress",
      "addressLocality": "New York",
      "addressCountry": "US"
    },
    {
      "@type": "PostalAddress",
      "addressLocality": "Berlin",
      "addressCountry": "DE"
    }
  ]
}

5. JobPosting Schema (Job Listings)

Critical for salary visibility. Add this to every job listing page.

Full Schema

{
  "@context": "https://schema.org",
  "@type": "JobPosting",
  "title": "Senior Software Engineer",
  "description": "<p>We're looking for a senior engineer to join our platform team...</p>",
  "identifier": {
    "@type": "PropertyValue",
    "name": "Acme Corp",
    "value": "12345"
  },
  "datePosted": "2026-02-20",
  "validThrough": "2026-04-20T23:59:59Z",
  "employmentType": ["FULL_TIME"],
  "hiringOrganization": {
    "@type": "Organization",
    "name": "Acme Corp",
    "sameAs": "https://acmecorp.com",
    "logo": "https://acmecorp.com/logo.png"
  },
  "jobLocation": {
    "@type": "Place",
    "address": {
      "@type": "PostalAddress",
      "streetAddress": "123 Tech Street",
      "addressLocality": "London",
      "addressRegion": "England",
      "postalCode": "EC1A 1BB",
      "addressCountry": "GB"
    }
  },
  "baseSalary": {
    "@type": "MonetaryAmount",
    "currency": "GBP",
    "value": {
      "@type": "QuantitativeValue",
      "minValue": 85000,
      "maxValue": 105000,
      "unitText": "YEAR"
    }
  },
  "responsibilities": "Design and build scalable backend systems. Mentor junior engineers. Review code and architecture decisions.",
  "skills": "Python, PostgreSQL, Docker, Kubernetes, AWS",
  "qualifications": "5+ years backend engineering. Experience with high-scale distributed systems.",
  "educationRequirements": {
    "@type": "EducationalOccupationalCredential",
    "credentialCategory": "bachelor degree"
  },
  "experienceRequirements": {
    "@type": "OccupationalExperienceRequirements",
    "monthsOfExperience": 60
  },
  "applicantLocationRequirements": {
    "@type": "Country",
    "name": "GB"
  },
  "jobLocationType": "TELECOMMUTE",
  "applicationContact": {
    "@type": "ContactPoint",
    "email": "jobs@acmecorp.com"
  }
}

Critical Fields for AI

Field	Impact	Why
`title`	High	AI uses this to match candidate queries
`baseSalary`	Critical	This is what AI cites when asked "What does [Company] pay?"
`jobLocation`	High	AI uses for location-based queries
`employmentType`	Medium	Full-time vs. contract vs. part-time
`datePosted`	Medium	Freshness signal for AI
`validThrough`	Medium	Tells AI if role is still open

Salary Field Variations

Salary Range:

"baseSalary": {
  "@type": "MonetaryAmount",
  "currency": "GBP",
  "value": {
    "@type": "QuantitativeValue",
    "minValue": 85000,
    "maxValue": 105000,
    "unitText": "YEAR"
  }
}

Hourly Rate:

"baseSalary": {
  "@type": "MonetaryAmount",
  "currency": "GBP",
  "value": {
    "@type": "QuantitativeValue",
    "value": 45,
    "unitText": "HOUR"
  }
}

Monthly Salary:

"baseSalary": {
  "@type": "MonetaryAmount",
  "currency": "GBP",
  "value": {
    "@type": "QuantitativeValue",
    "value": 7500,
    "unitText": "MONTH"
  }
}

6. FAQPage Schema (Careers Page)

Add this to your careers page to help AI answer common candidate questions.

Full Schema

{
  "@context": "https://schema.org",
  "@type": "FAQPage",
  "mainEntity": [
    {
      "@type": "Question",
      "name": "What is it like to work at Acme Corp?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "We're a 250-person fintech based in London. Engineers work in small teams (4-6 people), ship weekly, and choose their own tools. Culture is collaborative, low-ego, and focused on shipping."
      }
    },
    {
      "@type": "Question",
      "name": "What does Acme Corp pay for senior engineers?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "Senior Software Engineer: £85,000-£105,000. Staff Engineer: £105,000-£130,000. Principal Engineer: £130,000-£160,000. All ranges include base salary only, excluding equity."
      }
    },
    {
      "@type": "Question",
      "name": "What benefits does Acme Corp offer?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "28 days holiday + UK bank holidays. Private health insurance (Vitality). £1,500/year learning budget. 5% pension contribution. Work from home 3 days/week."
      }
    },
    {
      "@type": "Question",
      "name": "Does Acme Corp allow remote work?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "Yes. Hybrid model: 2 days/week in our London office, 3 days work from anywhere in the UK. Fully remote available for senior+ roles on a case-by-case basis."
      }
    },
    {
      "@type": "Question",
      "name": "What is Acme Corp's interview process?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "Four stages: (1) 30-minute recruiter screen, (2) 60-minute technical interview, (3) Take-home project (4-6 hours), (4) On-site final round (3 hours). Total timeline: 2-3 weeks from application to offer."
      }
    }
  ]
}

Best Practices

Do:

✅ Answer the exact questions candidates ask AI
✅ Be specific (numbers, names, details)
✅ Include salary information
✅ Use plain language, not marketing jargon

Don't:

❌ Write vague answers ("competitive compensation")
❌ Use questions nobody asks ("What makes us special?")
❌ Hide behind "contact us for details"

7. EmployerAggregateRating Schema

If you have Glassdoor reviews, add this to your careers page.

Full Schema

{
  "@context": "https://schema.org",
  "@type": "Organization",
  "name": "Acme Corp",
  "aggregateRating": {
    "@type": "AggregateRating",
    "ratingValue": "4.2",
    "ratingCount": "347",
    "bestRating": "5",
    "worstRating": "1"
  }
}

Note: Only add this if you actually have review data. Don't fabricate ratings — Google will penalize you.

8. BreadcrumbList Schema

Add to every page for navigation context.

Full Schema

{
  "@context": "https://schema.org",
  "@type": "BreadcrumbList",
  "itemListElement": [
    {
      "@type": "ListItem",
      "position": 1,
      "name": "Home",
      "item": "https://acmecorp.com"
    },
    {
      "@type": "ListItem",
      "position": 2,
      "name": "Careers",
      "item": "https://acmecorp.com/careers"
    },
    {
      "@type": "ListItem",
      "position": 3,
      "name": "Senior Software Engineer",
      "item": "https://acmecorp.com/careers/senior-software-engineer"
    }
  ]
}

9. Validation & Testing

Before deploying, validate your structured data:

Tools

1. Google Rich Results Test

URL: https://search.google.com/test/rich-results
Paste your URL or code
Checks for errors and warnings

2. Schema Markup Validator

URL: https://validator.schema.org/
Validates against official schema.org spec
More strict than Google's tool

3. OpenRole Schema Checker (Coming Soon)

Checks employer-specific fields
Verifies AI-readable formatting

Common Validation Errors

Error: "Missing required field"

{
  "@context": "https://schema.org",
  "@type": "Organization"
  // Missing "name" — required!
}

Fix: Add all required fields (name, url, logo for Organization).

Error: "Invalid date format"

"datePosted": "20/02/2026"  // Wrong format

Fix: Use ISO 8601 format:

"datePosted": "2026-02-20"

Error: "Unexpected property"

{
  "@type": "Organization",
  "companyVibe": "chill"  // Not a valid schema.org property
}

Fix: Use only official schema.org properties, or remove custom fields.

10. Common Mistakes

Mistake 1: Not Including Salary Data

Bad:

{
  "@type": "JobPosting",
  "title": "Senior Engineer"
  // No baseSalary field
}

Why it's bad: AI will guess your salary (and get it wrong).

Fix: Always include baseSalary with min/max range.

Mistake 2: Vague Descriptions

Bad:

"description": "We cultivate a dynamic, synergistic environment where innovation thrives."

Why it's bad: AI can't extract facts from marketing fluff.

Fix:

"description": "250-person fintech. Engineers work in teams of 5-7, ship weekly, choose their own tools."

Mistake 3: Outdated Information

Bad:

"numberOfEmployees": 150  // You now have 250

Why it's bad: AI will cite old data.

Fix: Update schema quarterly.

Mistake 4: Multiple Conflicting Schemas

Bad:

<script type="application/ld+json">
{"@type": "Organization", "name": "Acme Corp", "numberOfEmployees": 150}
</script>
<script type="application/ld+json">
{"@type": "Organization", "name": "Acme Corp", "numberOfEmployees": 250}
</script>

Why it's bad: AI doesn't know which is correct.

Fix: One schema per page (or merge into single JSON-LD block).

Mistake 5: Hiding Salary Data Behind "Apply to Learn More"

Bad: JobPosting schema with no baseSalary, expecting candidates to apply first.

Why it's bad: AI can't extract salary → AI guesses → candidate sees wrong number.

Fix: Publish broad ranges. You can still negotiate within the range.

11. Maintenance & Updates

Structured data isn't set-and-forget. Here's the maintenance schedule:

Weekly

Add JobPosting schema to new job listings
Remove or update validThrough dates for filled roles

Monthly

Validate all schema markup (Google Rich Results Test)
Check for new errors in Google Search Console
Update any facts that changed (e.g., employee count)

Quarterly

Review and update Organization schema
Update FAQPage answers if process/policy changed
Refresh salary ranges in JobPosting schemas

Annually

Full schema audit (all pages)
Update foundingDate, numberOfEmployees, etc.
Add new schema types if applicable (e.g., new pages)

Quick Start Checklist

Week 1:

Implement Organization schema on homepage
Validate with Google Rich Results Test
Deploy

Week 2:

Add FAQPage schema to careers page
Validate
Deploy

Week 3:

Add JobPosting schema to top 5 open roles (with salary data)
Validate each
Deploy

Week 4:

Add JobPosting to all remaining open roles
Add BreadcrumbList to key pages
Run full site validation

Ongoing:

Monitor what AI says about you (OpenRole audit)
Update schema when facts change
Add schema to new pages as you publish them

Conclusion

Structured data is your most direct way to control what AI says about your company.

It's not marketing. It's not "hoping AI finds you." It's giving AI the facts in the format it trusts most.

Companies that implement this see:

30-40% improvement in factual accuracy
32% higher citation rates
Immediate impact (within weeks of deployment)

Start with Organization schema on your homepage. Add FAQPage to your careers page. Include salary data in JobPosting schemas.

Then measure. Run a OpenRole audit before and 30 days after. You'll see the difference.

Resources

Schema.org Documentation:

Validation Tools:

Code Generators:

Further Reading:

Questions? Found an error? Want to share your implementation?
Email: engineering@openrole.co.uk

We maintain this guide publicly and update it as schema.org standards evolve. Pull requests welcome.

Structured Data for Employer Brands: A Technical Guide to JSON-LD

Structured Data for Employer Brands: A Technical Guide to JSON-LD

Table of Contents

1. What is JSON-LD and Why It Matters

What is JSON-LD?

Why JSON-LD vs. Microdata or RDFa?

Why It Matters for Employer Brands

2. Schema.org Vocabulary for Employers

3. Implementation: Step-by-Step

Option 1: Direct HTML Injection

Option 2: React/Next.js Component

Option 3: Server-Side Injection (PHP/Laravel/Rails)

Option 4: CMS Plugins

4. Organization Schema (Homepage)

Minimum Viable Schema

Full Schema (Recommended)

Field Explanations

For Multi-Location Companies

5. JobPosting Schema (Job Listings)

Full Schema

Critical Fields for AI

Salary Field Variations

6. FAQPage Schema (Careers Page)

Full Schema

Best Practices

7. EmployerAggregateRating Schema

Full Schema

8. BreadcrumbList Schema

Full Schema

9. Validation & Testing

Tools

Common Validation Errors

10. Common Mistakes

Mistake 1: Not Including Salary Data

Mistake 2: Vague Descriptions

Mistake 3: Outdated Information

Mistake 4: Multiple Conflicting Schemas

Mistake 5: Hiding Salary Data Behind "Apply to Learn More"

11. Maintenance & Updates

Weekly

Monthly

Quarterly

Annually

Quick Start Checklist

Conclusion

Resources