Greenhouse Jobs Scraper: Workday, Lever + Visa Flags

What does Greenhouse & Workday Jobs Scraper do?

Career site job scraper: Greenhouse jobs scraper, Workday jobs scraper and job listing API in one. Every job is flagged for visa sponsorship, US citizenship, ITAR and security clearance, with filters that skip those jobs before you pay.

What you can extract	Features & integrations
💼 Job basics: title, company, department, team	8 ATSs, one schema: board URLs, careers pages or company slugs
📍 Location: locations, remote flag, employment type	Filters: keywords, departments, locations, remote only
💰 Salary range: when the board publishes one	Skip before you pay: drop no-sponsorship or clearance jobs
📅 Posted date & apply URL: link straight to the application	Only new jobs: daily job alerts with posted-within filter
📝 Description: plain text and Markdown	Scheduling: run it hourly, daily or weekly with Apify schedules
🛂 Visa sponsorship flag: offered or not offered, with the evidence sentence	Export anywhere: JSON, CSV, Excel, XML or HTML from the dataset
🇺🇸 Citizenship / ITAR / clearance flags: each with the sentence it came from	API & SDKs: Apify REST API plus JavaScript and Python clients
🏢 Source ATS: Greenhouse, Lever, Ashby, Workday and 4 more	AI agents (MCP): call it from Claude or other agents via Apify's MCP server

Try it free in 1 click: open this ready-made example and press Start. Apify's free plan includes $5 of usage every month, no credit card needed. The Input example below returned 16 records and costs about $0.02 at list price.

It is a jobs scraper that pulls job postings straight from company career boards, then flags each job for visa sponsorship, US citizenship, ITAR and security clearance.

• Greenhouse jobs scraper, Lever jobs scraper, Ashby jobs scraper and Workday jobs scraper, plus Workable, SmartRecruiters, Recruitee and Personio, all in one normalized schema
• One job API across 8 ATSs: instead of calling and parsing each board's own API yourself, you send board URLs, careers pages or bare company slugs (stripe, ramp, notion) and get one format back
• Visa sponsorship jobs filter: workAuthorization on every job (sponsorship offered / not_offered, US citizenship, US person / ITAR, export control, security clearance required / preferred) with the evidence sentence. excludeNoSponsorship and excludeCitizenshipOrClearance drop those jobs before they are charged. In our test on 6 boards, 19 of 72 engineering jobs were dropped by those switches
• Workday career sites: paste a *.myworkdayjobs.com URL (NVIDIA, Target, CrowdStrike, Workday…) and get the same clean schema, with full description, exact post date and every location
• Auto-detect: a bare company slug is matched to the ATS the company uses (Workday needs its careers-site URL). Careers-page detection: paste https://ramp.com/careers and it finds the linked or embedded board
• Salary / compensation: structured pay from Ashby and Lever, plus pay ranges found in the description text for Greenhouse and others (compensation.source tells you which)
• Job alerts with only new jobs: turn on onlyNewJobs and scheduled runs return just the openings you haven't seen yet, so you only pay for new jobs
• Filters: title keywords (include and exclude), location contains, remote only, department/team, posted within N days, max jobs per company
• No duplicates: the same job reached through two inputs (say stripe and boards.greenhouse.io/stripe) is saved once
• No login, no browser, no proxies: uses each ATS's public JSON job-board API and runs in 256 MB, with retries, backoff and polite per-host rate limiting
• LLM- and AI-agent-ready: descriptions as clean Markdown, callable through the Apify MCP server

The work-authorization flags come from plain-text rules on the job description, not AI, so check evidence before you rely on a flag. Jobs without a description get workAuthorization: null.

What data can Greenhouse & Workday Jobs Scraper extract?

🏷️ type: job or error	🧩 ats: Which ATS the board runs on	🏢 company: Company name
🔤 companySlug: Company slug on the ATS	🆔 jobId: The ATS's own job ID	💼 title: Job title
🗂️ department: Department	👥 team: Team	📍 location: Main location
🗺️ locations: Every listed location	🌍 country: Country when the ATS gives one	🏠 remote: Remote flag (true/false)
🏢 workplaceType: On-site, hybrid or remote, as the ATS says	⏱️ employmentType: Full-time, contract and so on	💰 compensation: Salary range: summary, min, max, currency, interval, source
📅 postedAt: Date posted	🔄 updatedAt: Last updated, when given	🔗 jobUrl: Job page
✅ applyUrl: Direct apply link	📋 boardUrl: The company's job board	📝 descriptionText: Description as plain text
🧾 descriptionMarkdown: Description as Markdown	🧱 descriptionHtml: Original HTML (with includeHtml)	🕒 scrapedAt: When it was scraped
🛂 workAuthorization.sponsorship: Visa sponsorship: offered, not_offered or null	🇺🇸 workAuthorization.usCitizenshipRequired: US citizenship required	🛡️ workAuthorization.usPersonRequired: US person / ITAR required
📦 workAuthorization.exportControlled: Export-controlled role	🔐 workAuthorization.securityClearance: Clearance: required, preferred or null	🔎 workAuthorization.evidence: The sentences each flag came from

How to use Greenhouse & Workday Jobs Scraper in 5 steps

1. Create a free Apify account.
2. Open Greenhouse & Workday Jobs Scraper.
3. Add your input: board URLs (https://boards.greenhouse.io/stripe, https://nvidia.wd5.myworkdayjobs.com/NVIDIAExternalCareerSite), careers pages or slugs like notion, plus optional filters. Need visa sponsorship, or can't hold a clearance? Switch on Skip jobs that say no visa sponsorship and/or Skip jobs that need US citizenship, US-person (ITAR) status or a clearance. For alerts, switch on Only new jobs since last run.
4. Click Start.
5. Download the results as JSON, CSV or Excel (or use the API), or schedule the run daily so each run brings only the new openings.

Input

This exact input was run on Oct 19 2026 (256 MB): one real Greenhouse board and one board that doesn't exist, to show both a job and an error item. Paste it into the Input tab (JSON view) and click Start.

{
  "companies": [
    "https://boards.greenhouse.io/affirm",
    "https://boards.greenhouse.io/zzznotreal123"
  ],
  "keywords": ["engineer"],
  "maxJobsPerCompany": 15,
  "includeDescription": true
}

Ready-made example Tasks (open one and click Start):

• Find remote frontend jobs at top startups
• Track new engineering jobs posted this week
• Benchmark product manager salaries from job boards
• Scrape Workday jobs from a company career site
• New job alerts from company career pages

Supported inputs

ATS	Accepted formats
Greenhouse	boards.greenhouse.io/stripe, job-boards.greenhouse.io/airbnb, .../jobs/<id>, embed ?for=<slug>, ?gh_jid=<id>
Lever	jobs.lever.co/spotify, jobs.lever.co/<slug>/<postingId>, jobs.eu.lever.co/<slug>
Ashby	jobs.ashbyhq.com/ramp, jobs.ashbyhq.com/<slug>/<jobId>
Workable	apply.workable.com/<slug>, apply.workable.com/<slug>/j/<shortcode>, <slug>.workable.com
SmartRecruiters	jobs.smartrecruiters.com/<CompanyId>, careers.smartrecruiters.com/<CompanyId>
Recruitee	<slug>.recruitee.com, <slug>.recruitee.com/o/<offer>
Personio	<slug>.jobs.personio.de, <slug>.jobs.personio.com, .../job/<id>
Workday	<tenant>.wd5.myworkdayjobs.com/<Site> (any wdN, with or without /en-US/), .../job/<location>/<title>_<id>, wd1.myworkdaysite.com/recruiting/<tenant>/<Site>
Any except Workday	bare slug, e.g. stripe, notion, Ubisoft2 (tries Greenhouse → Lever → Ashby → SmartRecruiters → Workable → Recruitee → Personio)
Company site	a careers page URL such as https://ramp.com/careers (scanned for a linked or embedded board, including Workday)

Input fields

Field	Description
companies	Board URLs, job URLs, careers pages or bare slugs (required)
keywords / excludeKeywords	Title must contain any keyword / none of the excluded ones (case-insensitive)
locations	Any location of the job contains any of these strings
remoteOnly	Only jobs flagged remote
departments	Department or team contains any of these
postedWithinDays	Only jobs first published in the last N days (0 = any)
maxJobsPerCompany	Cap per company after filters (default 500, 0 = no limit)
includeDescription	Description as descriptionText + descriptionMarkdown (default on)
includeHtml	Also keep the original description HTML
atsToTry	Which ATSs to try for bare slugs, in order
detectFromCareerPage	Scan non-ATS URLs for an embedded board (default on)
excludeNoSponsorship	Skip jobs whose description says visa sponsorship is not available
excludeCitizenshipOrClearance	Skip jobs that need US citizenship, US-person (ITAR) status or a security clearance
onlyNewJobs	Output only jobs not returned by an earlier run with the same memory (default off). The first run returns everything and saves the baseline
stateKey	Optional name for that memory, e.g. frontend-alerts. Empty = one memory per company list

Output

Every record has a type: job or error. A real record from the run above (description shortened):

{
  "type": "job",
  "ats": "greenhouse",
  "company": "Affirm",
  "companySlug": "affirm",
  "jobId": "8010489003",
  "title": "Analytics Engineer II",
  "department": "Accounting",
  "team": null,
  "location": "Remote Spain",
  "locations": [
    "Remote Spain",
    "Remote Poland"
  ],
  "country": null,
  "remote": true,
  "workplaceType": null,
  "employmentType": null,
  "compensation": {
    "summary": "€63,000 - €99,000",
    "min": 63000,
    "max": 99000,
    "currency": "EUR",
    "interval": "YEAR",
    "source": "description"
  },
  "postedAt": "2026-10-01T14:33:52.000Z",
  "updatedAt": "2026-10-16T21:13:47.000Z",
  "jobUrl": "https://job-boards.greenhouse.io/affirm/jobs/8010489003",
  "applyUrl": "https://job-boards.greenhouse.io/affirm/jobs/8010489003",
  "boardUrl": "https://job-boards.greenhouse.io/affirm",
  "scrapedAt": "2026-10-20T01:40:57.996Z",
  "workAuthorization": {
    "sponsorship": "offered",
    "usCitizenshipRequired": false,
    "usPersonRequired": false,
    "exportControlled": false,
    "securityClearance": null,
    "evidence": [
      "We are able to offer visa sponsorship for this role, but do require that someone is based in Spain for the role."
    ]
  },
  "descriptionText": "At Affirm, we exist for the moments that matter—giving people a clear, predictable way to pay over time, with no hidden  ...",
  "descriptionMarkdown": "At Affirm, we exist for the moments that matter—giving people a clear, predictable way to pay over time, with no hidden  ..."
}

A clearance example from an earlier test run (SpaceX board, Oct 18 2026, trimmed):

{
  "company": "SpaceX",
  "ats": "greenhouse",
  "title": "AI Engineer, Special Programs",
  "location": "Washington, DC",
  "workAuthorization": {
    "sponsorship": null,
    "usCitizenshipRequired": false,
    "usPersonRequired": true,
    "exportControlled": true,
    "securityClearance": "required",
    "evidence": [
      "- To conform to US Government export regulations, applicant must be a (i) US citizen or national, (ii) US lawful, permanent resident (aka green card holder), (iii) Refugee under 8 USC.",
      "- This position requires successfully obtaining and maintaining a Top Secret Security Clearance as a condition of employment.",
      "ITAR REQUIREMENTS:"
    ]
  },
  "applyUrl": "https://boards.greenhouse.io/spacex/jobs/8557208002?gh_jid=8557208002"
}

You can download the dataset as JSON, CSV, Excel, XML or HTML.

How can I use the data?

• Job aggregation: build a niche job board (remote, AI, climate, frontend, startups) from hundreds of company boards
• Visa sponsorship job search: keep only jobs that don't rule out sponsorship, or that need no clearance
• HR tech and recruiting: hiring signals, competitor hiring trends, headcount by department and location
• Sales intelligence: find companies hiring for roles that signal they need your product
• Salary research: collect pay ranges for a role across companies
• AI agents and job-search copilots: feed fresh, structured postings to an LLM to match candidates to jobs
• Personal job search: watch your dream companies on a schedule and get only new matching roles

More Actors from the same developer

Actor	What it does
Telegram Channel Scraper	Public Telegram channel posts with a keyword monitor and only-new mode
Substack Scraper	Substack newsletters to clean Markdown, plus podcast transcripts
App Store & Google Play Reviews Scraper	Reviews from both stores in one run, only new reviews on schedules
Website to Markdown Crawler	Any website to Markdown for RAG, with incremental sync and llms.txt
Government Bids & RFP Scraper	Open bids and RFPs from 500+ US city and county portals on OpenGov
State Bids Scraper	Open bids from COMMBUYS, BidBuy, NJSTART, OregonBuys and NevadaEPro
PERM Green Card Sponsors	Companies that sponsor green cards, from official DOL PERM data

Error items

The run never silently returns nothing for an input: every input that can't be scraped gets one record with type: "error". The real error item from the run above:

{
  "type": "error",
  "input": "https://boards.greenhouse.io/zzznotreal123",
  "error": "BOARD_NOT_FOUND",
  "errorMessage": "No public greenhouse job board found for \"zzznotreal123\" (or it has no open jobs).",
  "ats": "greenhouse",
  "companySlug": "zzznotreal123",
  "scrapedAt": "2026-10-20T01:40:58.261Z"
}

Fields: type, input, error, errorMessage, scrapedAt, plus ats and companySlug when known, or tried (the ATSs checked) for bare slugs.

error	When
BOARD_NOT_FOUND	No public board (or job) found for that URL or slug
NO_OPEN_JOBS	The board exists but has no open jobs right now
JOB_NOT_FOUND	A job URL whose job is not open on that board
UNSUPPORTED_URL	Not a supported job board, and no board was found on the page
FETCH_FAILED	A request failed, a page couldn't be loaded, or an unexpected error

Filter them out with type = job. Error items are charged as dataset items (one per failed input). A RUN_SUMMARY record in the key-value store gives boards, jobs, errors, duplicatesSkipped, skippedSeenBefore and droppedByWorkAuthFilter. If the run reaches your maximum cost per run, it stops cleanly and logs it (no error item).

Tips

• Company slugs can differ from the company name (palantir on Lever, Ubisoft2 on SmartRecruiters). If a bare slug isn't found, paste the board URL or the company's careers page.
• For daily monitoring, schedule the actor with onlyNewJobs: true and your keywords: every run returns only openings it hasn't returned before. The memory lives in your own key-value store named ats-jobs-scraper-state; delete a key there (or change stateKey) to start fresh.
• Workday's list only says "3 Locations" for multi-location jobs. Keep includeDescription on (the default), or use a location filter, and the actor opens each kept job to fill in every location and the exact post date. Workday's public list shows at most 2,000 jobs per site, so add a keyword for very large employers.
• With exactly one keyword, SmartRecruiters is searched server-side, so even 5,000-job boards stay fast.
• Workable rate-limits aggressive traffic; the actor backs off automatically and reports FETCH_FAILED only if Workable keeps refusing.

FAQ

How much does it cost? Pay per event, no subscription: $0.001 per job saved to the dataset (error records are charged as dataset items too, one per failed input) and $0.00005 per run start. 1,000 jobs ≈ $1. Platform usage is included, so you don't pay compute on top. Set a maximum cost per run and the Actor stops cleanly when it's reached. See the Pricing tab.

Which integrations work? Any Apify integration: Make, Zapier, n8n, Google Sheets, Slack, webhooks, or schedules that run it hourly, daily or weekly.

Can I call it from the API? Yes. Node.js with apify-client:

import { ApifyClient } from 'apify-client';
const client = new ApifyClient({ token: 'YOUR_APIFY_TOKEN' });
const run = await client.actor('chimey_forearm/ats-jobs-scraper').call({
    companies: ['https://boards.greenhouse.io/affirm'],
    keywords: ['engineer'],
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

Python with apify-client:

from apify_client import ApifyClient
client = ApifyClient("YOUR_APIFY_TOKEN")
run = client.actor("chimey_forearm/ats-jobs-scraper").call(run_input={
    "companies": ["https://boards.greenhouse.io/affirm"],
    "keywords": ["engineer"],
})
items = client.dataset(run["defaultDatasetId"]).list_items().items
print(items)

Can I use it from an AI agent (MCP)? Yes. Add it to Claude or another MCP client through the Apify MCP server (https://mcp.apify.com?actors=chimey_forearm/ats-jobs-scraper). Output is flat JSON with Markdown descriptions, ideal for LLM tools.

Does it support Workday? Yes. Paste the company's Workday careers-site URL (for example https://nvidia.wd5.myworkdayjobs.com/NVIDIAExternalCareerSite); it uses Workday's public JSON endpoint, no browser. Bare slugs can't be guessed for Workday because each company picks its own site name. iCIMS and Taleo are not supported.

How does "only new jobs" work? The Actor saves the IDs of jobs it returned in a key-value store in your Apify account. The next run with the same company list (or the same stateKey) skips those IDs, so you only get, and only pay for, new postings. Changing filters can surface jobs that were filtered out before, as "new".

How do the visa / citizenship / clearance flags work? The Actor reads each job description for phrases like "visa sponsorship is not available", "unable to sponsor", "must be a US citizen", ITAR "US person" rules and "active TS/SCI clearance". Clearance mentioned as "beneficial" or "preferred" is marked preferred and is not dropped by the filter. It is rule-based text matching, not AI, so it can miss unusual wording; every flag carries the sentence it came from in evidence. Jobs without a description (for example Lever or Workday with includeDescription: false) get workAuthorization: null and are never dropped. Greenhouse descriptions are always read, so Greenhouse jobs are flagged even with descriptions turned off.

Is it legal? It reads public job-board data that companies publish for job seekers and aggregators through official public APIs. No login. Follow the terms of the sites you use and local law. Our Actors are ethical and do not extract any private user data, such as email addresses, gender, or location. They only extract what the user has chosen to share publicly. However, your results could contain personal data, which is protected by the GDPR in the European Union and by other regulations around the world. You should not scrape personal data unless you have a legitimate reason to do so. If you're unsure whether your reason is legitimate, consult your lawyers.

Found a bug or need a field? Open an issue in the Issues tab and I'll usually reply within a day.

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