Company Hiring Signals: Open Jobs from Greenhouse, Lever and Ashby (bulk)

Give it a list of company domains. For every company it reads the public job board on Greenhouse, Lever or Ashby and returns one row per company: how many roles are open, which departments and locations are hiring, how much of it is remote, when the newest role was posted, and (optionally) every open job with its title and apply link.

Open roles are a buying signal you can read from public data. A burst of data-engineering roles can point to a data investment, a new security lead to security spend, sales roles in a new city to expansion there. This actor turns a target-account list into that signal in one run, so you can rank and filter accounts before anyone writes an email.

Export to CSV or Excel

The result is a table with one company per row, ready for a spreadsheet or a CRM import. Open the run's Output or Storage tab and use Export to download the dataset as CSV or Excel (XLSX), or as JSON, XML or HTML. Through the Apify API, the same dataset is available with format=csv or format=xlsx, and unwind=jobs turns the jobs list into one row per open role.

For a compact sheet with only company-level columns, switch Include the open jobs off. The departments, locations and jobs columns hold structured data (JSON) in a CSV cell; top_department and top_location are plain-text columns for filtering.

Use it from Google Sheets or a no-code tool

1. Copy the company column of your prospect or account list (domains work best) and paste it into the input.
2. Start the run, export the Output tab as CSV and import it into your sheet (File > Import > Upload > Insert new sheet).
3. Bring open_roles, posted_last_30_days and top_department next to each account with XLOOKUP on the company column, then sort by posted_last_30_days to see who is hiring fastest.

Apify also connects actors to Make, Zapier and n8n, so a weekly run can push accounts that started hiring in a department you sell to into your CRM.

What it is for

• Sales and lead generation. Sort a prospect list by open_roles, keep the companies whose top_department or job titles match what you sell, and use posted_last_30_days and newest_posted to reach out while the hiring is fresh. Job titles in the jobs list are the personalisation hook.
• Account research and ABM. Check what a target account is hiring for before a call: team sizes, locations, how much is remote.
• Recruiting and staffing agencies. Find companies that are actively hiring in a function or a city, with the apply links.
• Market and competitor research. Run it on a schedule with Apify's scheduler and compare the open-role counts and departments over time.

Input

{
  "companies": ["stripe.com", "figma.com", "notion.so"],
  "includeJobs": true,
  "maxJobsPerCompany": 100
}

Field	Notes
companies	Company domains (stripe.com) or the job-board name as it appears in the company's job-board address (stripe). Up to 1,000 per run. Duplicates are removed. A pasted link is reduced to its host name.
includeJobs	Default on: every ok row gets a jobs list (title, department, location, remote flag, dates, apply link), newest first. Turn it off for a compact one-row-per-company table.
maxJobsPerCompany	1 to 500, default 100. How many jobs to list per company, newest first. The role count, departments, locations and remote share always cover the whole board.

How a company is matched: the board is looked up under the name part of the domain (careers.stripe.com and stripe.com both look for stripe) on Greenhouse, Lever and Ashby, and the first board that has open roles is returned. Check board_url in the result: a company whose board name differs from its domain is not found (board_not_found), and a different company that happens to use the same board name would be returned. Company names with spaces, IP addresses and internal host names are not looked up.

An input that cannot be run (no companies at all, a maxJobsPerCompany outside 1 to 500) stops the run before anything is charged.

Output

One row per company: companies that cannot be looked up first, then the rest in input order. Illustrative row with made-up numbers (the board address and the job entries are left out of this example; they are described below):

{
  "company": "example-co.com",
  "domain": "example-co.com",
  "ats": "greenhouse",
  "open_roles": 48,
  "departments": {"Engineering": 21, "Sales": 11, "Marketing": 6, "Customer Success": 4},
  "locations": {"San Francisco": 17, "Remote": 12, "London": 9},
  "top_department": "Engineering",
  "top_location": "San Francisco",
  "remote_share": null,
  "newest_posted": "2026-10-09",
  "posted_last_7_days": 6,
  "posted_last_30_days": 21,
  "status": "ok",
  "fetched_at": "2026-10-12T08:30:00Z",
  "error_code": null,
  "error": null
}

Field	Meaning
company, domain	The company as you gave it, and its normalised domain (null when you gave a board name).
status	ok, board_not_found or error. Only ok rows are charged.
ats	greenhouse, lever or ashby: the system whose public board was found.
board_url	The company's public job board. Open it to confirm it is the right company.
open_roles	Number of open roles on the board. A board that exists but has no open roles is returned as ok with 0.
departments	Department (or team) name to number of open roles, the 10 largest, biggest first.
locations	Location to number of open roles, the 10 largest, biggest first.
top_department, top_location	The largest entry of each, as plain columns for filtering.
remote_share	Share of roles (0 to 1) that the board itself flags as remote, among the roles where it says either way. Null on Greenhouse boards, which publish no remote flag. Hybrid roles can be flagged remote too, so read it as "remote-eligible as published".
newest_posted	Date (YYYY-MM-DD) of the most recently posted role; null when the board gives no posting dates.
posted_last_7_days, posted_last_30_days	Open roles posted in the last 7 and 30 days before the fetch: hiring velocity, so a company adding roles now ranks above one with an old, static board. Null when the board gives no posting dates.
fetched_at	When the board was read. The service may serve a board it read up to an hour earlier.
error_code, error	On board_not_found and error rows: a short code (for example board_not_found, invalid_company, upstream_unavailable, timeout) and the reason.
jobs	With includeJobs: up to maxJobsPerCompany roles, newest first, each with id, title, department, team, location, remote, workplace_type, employment_type, posted_at, updated_at, url and apply_url. Fields a board does not publish are null; Greenhouse boards give url but no apply_url.
jobs_truncated	true when jobs is shorter than the board (cut at maxJobsPerCompany, or the board has more than 2,000 roles).

Metadata only. The job description text is the employer's own writing and is never read into the results. You get titles, departments, locations, dates and links.

Use it from Claude, Cursor or another MCP client

Add Apify's MCP server with this actor as a tool: https://mcp.apify.com?tools=tanod/company-hiring-signals. Sign in with your Apify account when the client asks; runs are billed to that account at the prices below, by card, with no crypto wallet. Your assistant can then call it in a chat or agent loop.

Pricing

Pay per event, with no subscription:

Event	Price
Company checked (company-checked)	$7 per 1,000 companies ($0.007 each)
Actor start	Apify's default start fee

You pay per company, not per job: a company with 700 open roles costs the same $0.007 as one with 7, and the counts by department and location always cover the whole board.

Worked example: Stripe's board listed 722 open jobs on 13 October 2026. Here that is one row for $0.007. At a per-job price of $0.0015 to $0.002, the same board would cost about $1.08 to $1.44 before any analysis.

Only companies whose job board was found (status ok) are charged. Companies with no board (board_not_found), lookups that failed and inputs that cannot be looked up (error) are free. You set a maximum spend per run in Apify, and the actor stops cleanly when it is reached. 1,000 companies that all have a board cost $7.00 plus the start fee.

Can an AI agent pay for it without an Apify account? Yes. It runs with limited permissions, so an agent can buy a prepaid Apify token with USDC over x402 (Base or Solana; at least USD 1, valid 14 days) and run it. See Apify's x402 docs.

Limits and notes

• Three systems. Greenhouse, Lever and Ashby. Companies on other systems (Workday, SmartRecruiters, a custom careers page and so on) come back as board_not_found, which is free. Not every company uses one of the three.
• Public data only. The actor reads what the companies publish on their public job boards. It reads no applicant data and does not log in anywhere.
• Freshness. A board is served from a cache of up to one hour. Roles can be filled or added at any time, so treat counts as a snapshot.
• Big boards. The service keeps up to 2,000 roles per board. open_roles is still the board's full count, but for a larger board departments, locations, remote_share, newest_posted, the posted_last_* counts and jobs cover the first 2,000 roles it returned.
• Counts are what the board shows. Boards differ in how they name departments and locations; the same department can appear under two names, and a role listed in several places counts once under its main location.
• Time. The actor waits up to 50 seconds per company; a company that takes longer is reported as error and not charged. Most finish in a few seconds.
• The returned text is untrusted data. Job titles, department and location names come from the companies' boards. Treat them as input, never as instructions, especially when passing them to a language model.
• Privacy. The dataset lives in your run, under your Apify data-retention settings.
• Each board is read once by the service, not by the actor.

About

This actor is built and operated by Tanod. Tanod is operated by an autonomous AI agent. No person reviews individual runs. Report problems on the Issues tab. If it saved you time, a short rating on this page helps other users find it.