Greenhouse Job Scraper & API

Scrape Greenhouse ATS job boards via API and get clean, structured job data with department filtering applied before anything is stored. Pull live roles from Automattic, GitLab, Speechify, and thousands of other Greenhouse-hosted career sites. No browser, no HTML parsing, 100% open source. Built for job boards, AI agents, and hiring research.

What can Greenhouse Job Scraper & API do?

• ✅ Scrape job listings from any Greenhouse job board
• ✅ Filter by department before storing, so you only pay for jobs you keep
• ✅ Filter by recency (daysBack) for scheduled, incremental scraping
• ✅ Limit results per board with maxJobs
• ✅ Enhanced fields: multi-currency salary parsing, location arrays, remote/hybrid detection
• ✅ Export data in JSON, CSV, XML, Excel, or HTML
• ✅ 98%+ run success rate (the live stat is visible right on this page)
• ✅ 100% open source (MIT). Audit the code on GitHub

Why filtering before storing saves you money

Most Greenhouse scrapers fetch every job on a board and leave the filtering to you. You pay for Sales, HR, and Support listings you never wanted.

This actor uses Greenhouse's department API to filter first. A typical mid-size board lists 300+ jobs across all departments. If you only want Engineering:

Approach	Jobs stored	Cost per board
Fetch-everything scraper at ~$2.00/1,000	300	~$0.60, plus your own filtering work
This scraper at $2.00/1,000 with departments set	~20	~$0.04, already clean

Same per-result price, but you store only the jobs you asked for. The cost per relevant job is typically 10 to 15 times lower, and your dataset arrives ready to use.

Pricing

$2.00 per 1,000 results, pay per event. You are only charged for jobs that survive your filters, not for everything the board lists.

• 50 jobs = $0.10
• 500 jobs = $1.00
• 5,000 jobs = $10.00

Input

Simple Example

{
  "urls": [
    { "url": "https://job-boards.greenhouse.io/automatticcareers" },
    { "url": "https://job-boards.greenhouse.io/gitlab" }
  ]
}

With Filters (Per-Board)

Each URL can have its own filters:

{
  "urls": [
    {
      "url": "https://job-boards.greenhouse.io/automatticcareers",
      "departments": [307170],
      "maxJobs": 20,
      "daysBack": 7
    },
    {
      "url": "https://job-boards.greenhouse.io/gitlab",
      "maxJobs": 10
    }
  ]
}

Parameters

• urls (required): Array of job board configurations. Each object supports:
  • url (required): Clean Greenhouse job board URL (no query params needed)
  • departments (optional): Array of department IDs to filter (e.g., [307170, 307172])
  • maxJobs (optional): Maximum number of jobs to scrape from this board
  • daysBack (optional): Only fetch jobs updated in the last N days (e.g., 7 for last week)
• proxy (optional): Proxy configuration. Defaults to Apify proxy

How to Find Department IDs

1. Visit the company's Greenhouse job board (e.g., https://job-boards.greenhouse.io/automatticcareers)
2. Click on a department filter (e.g., "Code Wrangling" or "Account Executive")
3. Look at the URL bar. You'll see something like: ?departments[]=59798
4. The number (59798) is the department ID
5. Use that ID in your input: "departments": [59798]

Scheduled Runs

Keeping a board fresh is two parts that work together:

1. A Schedule sets when the actor runs. In Apify Console, open Schedules → Create new, add this actor (or a saved task with your input), and give it a cron expression. Weekly Monday 6am is 0 6 * * 1; Monday and Thursday is 0 6 * * 1,4. The schedule is what makes runs recur — the input JSON alone does not.
2. daysBack sets how far back each run looks, filtering jobs by their updated_at timestamp. Match it to your cron cadence so each run picks up everything new since the last one without re-storing old jobs: a weekly cron pairs with daysBack: 7, a twice-weekly cron with daysBack: 4. You only pay for jobs that pass the filter.

Input for a weekly schedule (0 6 * * 1):

{
  "urls": [
    {
      "url": "https://job-boards.greenhouse.io/automatticcareers",
      "departments": [307170],
      "daysBack": 7
    }
  ]
}

Input for a twice-weekly schedule (0 6 * * 1,4):

{
  "urls": [
    {
      "url": "https://job-boards.greenhouse.io/automatticcareers",
      "departments": [307170],
      "daysBack": 4
    }
  ]
}

Tip: set daysBack one or two days longer than your cron gap (e.g. daysBack: 9 on a weekly cron) so a delayed or skipped run doesn't leave a gap in coverage. Duplicates across runs are expected — dedupe on the id field downstream.

Multiple companies with different filters

{
  "urls": [
    {
      "url": "https://job-boards.greenhouse.io/automatticcareers",
      "departments": [307170],
      "maxJobs": 20
    },
    {
      "url": "https://job-boards.greenhouse.io/gitlab",
      "maxJobs": 10
    },
    {
      "url": "https://job-boards.greenhouse.io/shopify",
      "departments": [123, 456],
      "maxJobs": 15
    }
  ]
}

Output

Each job listing includes:

{
  "id": 6860572,
  "company": "automatticcareers",
  "type": "Full-time",
  "title": "Account Executive, WordPress VIP",
  "description": "<p>Job description HTML...</p>",

  "location": "Remote",
  "locations": ["Remote"],
  "isRemote": true,
  "isHybrid": false,

  "salary": {
    "min": 80000,
    "max": 120000,
    "currency": "USD",
    "raw": "$80k - $120k"
  },

  "department": "Account Executive",

  "metadata": {
    "Employment Type": "Full-time",
    "Experience Level": "Mid-Senior level"
  },

  "postingUrl": "https://job-boards.greenhouse.io/automatticcareers/jobs/6860572",
  "applyUrl": "https://job-boards.greenhouse.io/automatticcareers/jobs/6860572",
  "publishedAt": "2025-05-07T01:08:03.000Z"
}

Field Descriptions

Basic fields (always extracted):

• id, title, company, department, postingUrl, applyUrl, publishedAt

Enhanced fields (parsed from data):

• location (string) - Raw location text from Greenhouse
• locations (array) - Parsed location list (split on commas/slashes)
• isRemote (boolean) - Location contains "remote"
• isHybrid (boolean) - Location contains "hybrid"
• salary (object|null) - Regex extraction for salary ranges with currency detection
  • Handles: $110,000 - $120,000, £50k - £70k, €60,000 - €80,000
  • Detects currency from symbol (£=GBP, €=EUR) and context for $ (USD/CAD/AUD by region)
  • Only catches range patterns; narrative descriptions should be parsed with an LLM downstream
• metadata (object) - All Greenhouse metadata fields (Employment Type, Experience Level, etc.)

For LLM enhancement (recommended downstream post-processing):

• description - Full HTML description for extracting tech stack, detailed requirements, timezone restrictions
• location - Raw string for geographic classification (US-only, EMEA, APAC, etc.)
• salary - May be null if salary isn't in a simple format; parse description for complex patterns

Use it with AI agents

This actor works as a tool for AI agents through the Apify MCP server. Connect your agent (Claude, or any MCP-compatible framework) to the Apify MCP server and it can discover and call dalleyne/greenhouse-job-scraper with the same JSON input shown above. The input schema is deliberately small (one urls array), which keeps agent tool calls reliable.

Typical agent patterns:

• Career chatbots that answer "who is hiring engineers at Greenhouse-hosted companies this week?"
• Talent-market research pipelines that track posting volume by department
• Job board back ends that refresh listings on a schedule without scraping infrastructure

Is it legal to scrape Greenhouse job listings?

This actor reads public job postings through Greenhouse's official public job board API, the same data anyone can see in a browser without logging in. It collects no personal data. You are responsible for how you use the data; if in doubt, review Greenhouse's terms and the rules that apply to your use case.

How It Works

1. Parses Greenhouse job board URLs and extracts the board token (e.g., "automatticcareers")
2. Fetches departments via Greenhouse's public API: https://boards-api.greenhouse.io/v1/boards/{token}/departments
3. Filters by department IDs if specified in the input
4. For each remaining job, fetches full details including description and metadata
5. Parses enhanced fields (salary, location array, remote/hybrid flags)
6. Saves results to the dataset

Usage via API

curl -X POST https://api.apify.com/v2/acts/dalleyne~greenhouse-job-scraper/runs \
  -H "Authorization: Bearer YOUR_API_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "urls": [
      {
        "url": "https://job-boards.greenhouse.io/automatticcareers",
        "departments": [307170]
      }
    ]
  }'

Run It Locally (Open Source)

The full source is on GitHub:

# Install dependencies
npm install

# Set up local Apify storage
export APIFY_LOCAL_STORAGE_DIR=./apify_storage

# Create input file
mkdir -p ./apify_storage/key_value_stores/default
echo '{"urls":[{"url":"https://job-boards.greenhouse.io/automatticcareers","departments":[307170]}]}' > ./apify_storage/key_value_stores/default/INPUT.json

# Run the actor
npm start

# Check results
cat ./apify_storage/datasets/default/*.json

FAQ

How much does a typical run cost?

A scheduled run pulling new engineering jobs from 6 companies typically stores 10 to 50 jobs, which costs $0.02 to $0.10. Because filtering happens before storage, board size doesn't drive your bill. Job relevance does.

How do I keep a job board updated automatically?

Create a Schedule in Apify Console pointing at this actor, and set daysBack to match your cadence (7 for weekly, 4 for twice-weekly). Each run then only fetches and charges for jobs updated since your last window.

How do I find a company's department IDs?

Click a department filter on their job board and copy the number from the URL. The step-by-step guide above has details.

What if a salary isn't extracted?

The built-in parser catches range patterns in 30+ currencies' symbols (e.g., $110,000 - $120,000, £50k - £70k). Narrative compensation text is left in description for you to parse downstream with an LLM.

Can AI agents run this actor?

Yes. It's callable through the Apify MCP server like any store actor, and the single-array input schema keeps tool calls simple. See Use it with AI agents.

Is this actor maintained?

Yes. It powers GlobalRemote, the author's own job board, twice a week. If the scraper breaks, his site breaks, so it gets fixed fast. Report anything via the Issues tab or GitHub Issues.

Changelog

See CHANGELOG.md. Latest: documentation overhaul and store listing refresh (June 2026).

Related Scrapers

Looking for other ATS platforms?

• Ashby Job Scraper & API - Scrape Ashby job boards (Buffer, Zapier, RevenueCat, etc.) with team filtering and applicant location requirements

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License

MIT

Author

Built by Damien Alleyne