# Greenhouse Job Board Listings Scraper (`scrapers_lat/greenhouse-jobs-scraper`) Actor
Scrape Greenhouse job board listings by company board token. Extract job title, location, department, offices, requisition ID, posting date, apply URL and full HTML description. Filter by keyword. Export JSON, CSV or Excel. No login or API key.
- **URL**: https://apify.com/scrapers\_lat/greenhouse-jobs-scraper.md
- **Developed by:** [Scrapers Lat](https://apify.com/scrapers_lat) (community)
- **Categories:** Jobs, Lead generation, Automation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet
## Pricing
from $2.00 / 1,000 results
This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.
Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event
## What's an Apify Actor?
Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".
## How to integrate an Actor?
If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.
In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md):
```bash
npm install apify-client
```
In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md):
```bash
pip install apify-client
```
In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md):
````bash
# MacOS / Linux
curl -fsSL https://apify.com/install-cli.sh | bash
# Windows
irm https://apify.com/install-cli.ps1 | iex
```bash
In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md).
If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md).
For usage examples, see the [API](#api) section below.
For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).
# README
[](https://console.apify.com/actors/BhybNbJDIpxddhodt/input)
## Greenhouse Job Board Listings Scraper
> Extract every open job from any company hiring on Greenhouse ATS, straight from the public board, with title, location, department and full description
18 fields per record
Any company on Greenhouse
JSON / CSV / Excel output formats
Updated 2026-07-03
### What you get
Point the scraper at one or more Greenhouse board tokens (the company slug in a boards.greenhouse.io URL, for example stripe, airbnb or figma) and get every open role on that board as a structured record:
- **title**: the job title
- **company**: the hiring company name
- **location**: the office or work location for the role
- **department\***: the primary department the role sits in
- **departments\***: every department tag on the role
- **offices\***: office names attached to the role
- **url**: the public apply URL for the job
- **jobId**: the Greenhouse job posting ID
- **internalJobId**: the company's internal Greenhouse job ID
- **requisitionId**: the employer's requisition or opening ID
- **boardToken**: the company board token the job came from
- **updatedAt**: when the posting was last updated
- **firstPublished**: when the posting first went live
- **applicationDeadline**: the application close date when the employer sets one
- **content\***: the full job description as HTML
- **descriptionText\***: the full job description as clean plain text
- **metadata\***: custom fields the employer attaches to the posting
- **observedAt**: when this listing was last seen by the scraper
*\*These fields only appear when Fetch full job description is set to true.*
### Who is it for
| Use case | Who benefits |
|---|---|
| Track open roles at target companies for candidate outreach | Recruiters and staffing agencies |
| Read hiring signals to time sales and prospecting | Sales and revenue teams |
| Monitor competitor headcount and team growth | Market and competitive researchers |
| Build a live job board or ATS aggregator feed | Job board and marketplace builders |
| Analyze roles, locations and departments at scale | Talent and labor market analysts |
### Frequently Asked Questions
**What is a Greenhouse board token and how do I find it?**
The board token is the company slug in its Greenhouse careers URL. If a company applies through boards.greenhouse.io/stripe, the token is stripe. You can paste the token, the full URL, or the slug and the scraper will normalize it. Add one token per company you want to scrape.
**How many jobs can it return per company?**
It returns every open role on the board, which ranges from a few dozen to several hundred per company. Use Max Items to cap the total across all board tokens when you only need a sample.
**Can I scrape several companies in one run?**
Yes. Add multiple board tokens and the scraper collects jobs from each board in turn, tagging every record with its boardToken so you can tell them apart. The Max Items limit applies to the combined total.
**How do I filter to specific roles?**
Use the Keyword filter to keep only jobs whose title, department, location or description contain your keyword, for example "engineer", "remote" or "sales". Leave it empty to return every open job.
**What happens if a board token does not exist?**
The scraper records an error row for that token with the reason and moves on to the next company, so one bad token never stops the run.
### Export, API and AI agents (x402 + MCP)
Export the scraped data to **JSON, CSV or Excel**, pull it as a **dataset** through the Apify **API**, or wire it into your app with **no code**. This web scraper and data extractor also works for bulk data extraction and scheduled runs.
For AI agents: this Actor is available on **x402**, Apify's agentic payment standard built with Coinbase. An AI agent can discover, pay for and run it on its own with a funded wallet and a single HTTP request: no account, no subscription, no API key and no human in the loop. It also runs as an **MCP** tool inside Claude, Cursor and other AI clients out of the box. Learn more about [x402 agentic payments on Apify](https://docs.apify.com/platform/integrations/x402).
### Related scrapers
Need data from the same space? Here are other scrapers we build and maintain:
- [Seek Australia Jobs & Salary Scraper](https://apify.com/scrapers_lat/seek-jobs-scraper): Job listings and salary data from Seek Australia and New Zealand.
- [Jora Jobs & Salary Scraper](https://apify.com/scrapers_lat/jora-jobs-scraper): Job postings and pay ranges across Jora in Australia, NZ and Asia.
- [GetOnBrd LATAM Tech Jobs Scraper](https://apify.com/scrapers_lat/getonbrd-scraper): Latin American tech job listings with salary data.
- [LinkedIn Jobs & Company Scraper](https://apify.com/scrapers_lat/linkedin-jobs-scraper): Job postings with company, seniority and location fields.
- [Crunchbase Company & Funding Scraper](https://apify.com/scrapers_lat/crunchbase-scraper): Company profiles, funding rounds and investor data.
- [Product Hunt Products & Makers Scraper](https://apify.com/scrapers_lat/product-hunt-scraper): Product launches, upvotes and maker profiles.
### More scrapers at scrapers.lat
This actor is built and maintained by [scrapers.lat](https://scrapers.lat), where we publish scrapers for Latin American and US public platforms: real estate, jobs, e-commerce, company registries and government data. Browse the full catalog, see live sample output for each one, or ask us for a custom scraper at [scrapers.lat](https://scrapers.lat).
---
> This actor is an independent tool and has no affiliation with Greenhouse. It only accesses data that is publicly available on company job boards. Use it in accordance with Greenhouse's terms of service.
# Actor input Schema
## `maxItems` (type: `integer`):
Maximum number of job listings to collect across all board tokens. Optional.
## `withDescription` (type: `boolean`):
When enabled, each job includes the full HTML description, plain-text description, departments, offices and metadata. When disabled, only the lightweight listing fields (title, location, apply URL, dates) are collected.
## `boardTokens` (type: `array`):
Greenhouse board tokens of the companies to scrape. The token is the company slug in its careers URL, for example boards.greenhouse.io/stripe means the token is "stripe". Add one token per company.
## `searchQuery` (type: `string`):
Optional keyword to filter jobs after they are fetched. Matches against the job title, department, location and description (case-insensitive). Leave empty to return every open job.
## Actor input object example
```json
{
"maxItems": 10,
"withDescription": true,
"boardTokens": [
"stripe",
"airbnb",
"figma"
]
}
````
# Actor output Schema
## `results` (type: `string`):
No description
# API
You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.
## JavaScript example
```javascript
import { ApifyClient } from 'apify-client';
// Initialize the ApifyClient with your Apify API token
// Replace the '' with your token
const client = new ApifyClient({
token: '',
});
// Prepare Actor input
const input = {
"maxItems": 10,
"boardTokens": [
"stripe",
"airbnb",
"figma"
],
"searchQuery": ""
};
// Run the Actor and wait for it to finish
const run = await client.actor("scrapers_lat/greenhouse-jobs-scraper").call(input);
// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
console.dir(item);
});
// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs
```
## Python example
```python
from apify_client import ApifyClient
# Initialize the ApifyClient with your Apify API token
# Replace '' with your token.
client = ApifyClient("")
# Prepare the Actor input
run_input = {
"maxItems": 10,
"boardTokens": [
"stripe",
"airbnb",
"figma",
],
"searchQuery": "",
}
# Run the Actor and wait for it to finish
run = client.actor("scrapers_lat/greenhouse-jobs-scraper").call(run_input=run_input)
# Fetch and print Actor results from the run's dataset (if there are any)
print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
print(item)
# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start
```
## CLI example
```bash
echo '{
"maxItems": 10,
"boardTokens": [
"stripe",
"airbnb",
"figma"
],
"searchQuery": ""
}' |
apify call scrapers_lat/greenhouse-jobs-scraper --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=scrapers_lat/greenhouse-jobs-scraper",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "Greenhouse Job Board Listings Scraper",
"description": "Scrape Greenhouse job board listings by company board token. Extract job title, location, department, offices, requisition ID, posting date, apply URL and full HTML description. Filter by keyword. Export JSON, CSV or Excel. No login or API key.",
"version": "0.1",
"x-build-id": "O0NjziMtGpruTrGYz"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/scrapers_lat~greenhouse-jobs-scraper/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-scrapers_lat-greenhouse-jobs-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/scrapers_lat~greenhouse-jobs-scraper/runs": {
"post": {
"operationId": "runs-sync-scrapers_lat-greenhouse-jobs-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/scrapers_lat~greenhouse-jobs-scraper/run-sync": {
"post": {
"operationId": "run-sync-scrapers_lat-greenhouse-jobs-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
}
},
"components": {
"schemas": {
"inputSchema": {
"type": "object",
"required": [
"boardTokens"
],
"properties": {
"maxItems": {
"title": "Max Items",
"minimum": 1,
"maximum": 1000000,
"type": "integer",
"description": "Maximum number of job listings to collect across all board tokens. Optional."
},
"withDescription": {
"title": "Fetch full job description",
"type": "boolean",
"description": "When enabled, each job includes the full HTML description, plain-text description, departments, offices and metadata. When disabled, only the lightweight listing fields (title, location, apply URL, dates) are collected.",
"default": true
},
"boardTokens": {
"title": "Company board tokens",
"type": "array",
"description": "Greenhouse board tokens of the companies to scrape. The token is the company slug in its careers URL, for example boards.greenhouse.io/stripe means the token is \"stripe\". Add one token per company.",
"items": {
"type": "string"
}
},
"searchQuery": {
"title": "Keyword filter",
"type": "string",
"description": "Optional keyword to filter jobs after they are fetched. Matches against the job title, department, location and description (case-insensitive). Leave empty to return every open job."
}
}
},
"runsResponseSchema": {
"type": "object",
"properties": {
"data": {
"type": "object",
"properties": {
"id": {
"type": "string"
},
"actId": {
"type": "string"
},
"userId": {
"type": "string"
},
"startedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"finishedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"status": {
"type": "string",
"example": "READY"
},
"meta": {
"type": "object",
"properties": {
"origin": {
"type": "string",
"example": "API"
},
"userAgent": {
"type": "string"
}
}
},
"stats": {
"type": "object",
"properties": {
"inputBodyLen": {
"type": "integer",
"example": 2000
},
"rebootCount": {
"type": "integer",
"example": 0
},
"restartCount": {
"type": "integer",
"example": 0
},
"resurrectCount": {
"type": "integer",
"example": 0
},
"computeUnits": {
"type": "integer",
"example": 0
}
}
},
"options": {
"type": "object",
"properties": {
"build": {
"type": "string",
"example": "latest"
},
"timeoutSecs": {
"type": "integer",
"example": 300
},
"memoryMbytes": {
"type": "integer",
"example": 1024
},
"diskMbytes": {
"type": "integer",
"example": 2048
}
}
},
"buildId": {
"type": "string"
},
"defaultKeyValueStoreId": {
"type": "string"
},
"defaultDatasetId": {
"type": "string"
},
"defaultRequestQueueId": {
"type": "string"
},
"buildNumber": {
"type": "string",
"example": "1.0.0"
},
"containerUrl": {
"type": "string"
},
"usage": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "integer",
"example": 1
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
},
"usageTotalUsd": {
"type": "number",
"example": 0.00005
},
"usageUsd": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "number",
"example": 0.00005
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
}
}
}
}
}
}
}
}
```