Job Postings Scraper - Greenhouse, Lever & Ashby (Multi-ATS)

Pull live job openings from any company that hires on Greenhouse, Lever, or Ashby. Give it a company slug, paste a careers-board URL, or let it auto-detect the platform for you. Every posting comes back as one clean, normalized row no matter which ATS it came from: title, location, department, team, employment type, remote flag, salary (where the ATS exposes it), the listing and apply URLs, created/updated dates, and the full description in both plain text and HTML. Export as JSON, CSV, or Excel.

It calls each ATS's own public job-board API directly instead of driving a headless browser, so it's fast, needs no login, and doesn't trip anti-bot. Mix as many boards and ATS types as you want in a single run.

Three ways to point it at a board

You can put any of these in the sources array, and mix them freely:

1. Explicit object — { "ats": "greenhouse", "company": "stripe" }
2. Pasted board URL — "https://jobs.lever.co/spotify" or "https://boards.greenhouse.io/stripe" (the ATS and slug are read straight out of the URL)
3. Bare company slug — "ramp" (the actor probes Greenhouse, Lever, and Ashby and uses whichever one has a board)

The company slug is the identifier in the careers-page URL: boards.greenhouse.io/stripe, jobs.lever.co/spotify, jobs.ashbyhq.com/ramp.

Underlying endpoints:

• greenhouse — boards-api.greenhouse.io/v1/boards/{company}/jobs
• lever — api.lever.co/v0/postings/{company}
• ashby — api.ashbyhq.com/posting-api/job-board/{company}

Filters

Narrow the run before anything is billed — filtered-out rows never cost you a thing:

• titleKeyword — title must contain this text
• locationKeyword — location must contain this text
• department — department or team must contain this text
• remoteOnly — keep only jobs detected as fully remote

Input

Field	Type	Description
sources	array	Board objects {ats, company}, board URLs, or bare slugs (any mix). Required.
titleKeyword	string	Keep only jobs whose title contains this (case-insensitive).
locationKeyword	string	Keep only jobs whose location contains this (case-insensitive).
department	string	Keep only jobs whose department or team contains this (case-insensitive).
remoteOnly	boolean	Keep only fully-remote jobs.
maxItems	integer	Stop after this many rows across all boards (0 = no limit).
impersonate	string	Browser TLS fingerprint (chrome by default).

{
  "sources": [
    { "ats": "greenhouse", "company": "stripe" },
    "https://jobs.lever.co/spotify",
    "ramp"
  ],
  "titleKeyword": "engineer",
  "remoteOnly": true,
  "maxItems": 500
}

Output fields

One row per posting. A check means the field is populated when that ATS provides it; otherwise it's null.

Field	Type	Greenhouse	Lever	Ashby
source_ats	string	✅	✅	✅
company	string	✅	✅	✅
job_id	string	✅	✅	✅
global_id	string {ats}:{company}:{job_id}	✅	✅	✅
title	string	✅	✅	✅
location	string	✅	✅	✅
department	string	✅	✅	✅
team	string	—	✅	✅
employment_type	string	—	✅	✅
remote	boolean	inferred	✅	✅
remote_type	remote/hybrid/onsite	inferred	✅	✅
salary	string	—	when set	when set
url	string (listing)	✅	✅	✅
apply_url	string	—	✅	✅
created_at	ISO 8601	✅	✅	✅
updated_at	ISO 8601	✅	—	when set
posted_at	ISO 8601	✅	✅	✅
scraped_at	ISO 8601	✅	✅	✅
description	plain text	✅	✅	✅
description_html	HTML	✅	✅	✅

global_id is stable across runs, so you can diff datasets or join against your own systems. Greenhouse's board API has no employment-type, team, or salary, no explicit remote flag, and no separate apply endpoint — remote/remote_type there are inferred from the location and title text (treat them as best-effort for that source), and apply_url is null since the listing url is the only link Greenhouse exposes.

Example output

{
  "source_ats": "lever",
  "company": "spotify",
  "job_id": "88499546-e9f7-4403-87a5-240050bd7c5b",
  "global_id": "lever:spotify:88499546-e9f7-4403-87a5-240050bd7c5b",
  "title": "Accounts Payable Analyst",
  "location": "New York, NY",
  "department": "Finance",
  "team": "Accounting",
  "employment_type": "Permanent",
  "remote": false,
  "remote_type": "hybrid",
  "salary": null,
  "url": "https://jobs.lever.co/spotify/88499546-e9f7-4403-87a5-240050bd7c5b",
  "apply_url": "https://jobs.lever.co/spotify/88499546-e9f7-4403-87a5-240050bd7c5b/apply",
  "created_at": "2026-05-11T11:20:11.285000+00:00",
  "updated_at": null,
  "posted_at": "2026-05-11T11:20:11.285000+00:00",
  "scraped_at": "2026-06-24T09:15:02.110000+00:00",
  "description": "Spotify is looking for an Accounts Payable Analyst ..."
}

Why this one

• One shape for every ATS. Greenhouse, Lever, and Ashby each return a different JSON structure; this maps all of them to the same fields, so you can dump multiple companies into one dataset and not care where each row came from.
• Paste a URL or just a name. No need to know which ATS a company uses — paste the careers link or the bare slug and it figures the rest out.
• Nothing fails silently. A wrong slug, a failed request, or an API that changes shape gives you a typed error row (fetch_failed, parse_failed, invalid_source, invalid_input) instead of a quietly empty run. One bad board never aborts the rest, but if every source fails the run is marked failed (not a green empty dataset), and a rate-limit/anti-bot block (HTTP 403/429/5xx) is reported as a block rather than a false "no board found".
• You're billed per valid posting delivered, so error rows, duplicates, and rows you filter out don't cost you anything.
• Duplicates are removed within a run, per ATS, by job id.

Notes

Only public, unauthenticated job-board APIs are used — the same data these companies publish on their own careers pages. Follow each provider's Terms and the laws that apply to you, and use the data responsibly.

Who built this

I build scrapers for my own projects and publish the ones that turn out genuinely useful. This is one of them. If you need a custom scraper, a data pipeline, or a change to this actor, I'm available for freelance work.

GitHub: github.com/bujhmml · Site: bujhmml.fun