Company Hiring Signals: Careers Pages & ATS Jobs

Find out which companies are hiring right now, and for what. Give it a list of company websites; for every company you get one row with:

• Is it hiring? true, false (the careers page says there are no openings, or the job board is empty) or null when it could not be told
• Careers page and job board (Greenhouse, Lever, Ashby, Workable, Personio, Recruitee, Breezy HR, BambooHR read in full; Workday, SmartRecruiters, Teamtailor, iCIMS, SuccessFactors and others recognised)
• Open jobs: title, department, location, country, remote, employment type, posted date and link, each with a job function (sales, engineering, marketing, finance …) and a seniority level (executive, VP, director, manager, senior, junior, intern …)
• Hiring signals ready for sales and recruiting: hiring_sales, hiring_engineering, hiring_leadership, high_volume_hiring, recent_postings, remote_roles, multi_country_hiring, your own keywords, and a hiring score from 0 to 100

It reads company websites in any language (English, German, French, Dutch, Spanish, Italian, Portuguese, Polish, Nordic and Hungarian careers pages are understood) and takes the output of Google Maps Scraper, Website Contacts Scraper or any dataset with a website column.

Who it is for

• B2B sales teams: a company that is hiring has budget and new problems. A company hiring five salespeople needs a CRM, sales tools and training; a company hiring engineers needs dev tools and cloud; one hiring its first HR manager needs payroll and HR software. Sort your account list by who is hiring for the role your product serves.
• Recruitment agencies: find the companies that are hiring for the roles you place, with the job links, before your competitors call them.
• Investors and market research: which companies in a sector are growing, and in which functions and countries.
• Agencies and freelancers: a company hiring a marketing manager or a developer is a company that needs that work done now.

How it works

1. Each company website is opened at its homepage. The crawler looks for the careers page first (Careers, Jobs, Karriere, Emplois, Vacatures, Werken bij …), and opens nothing else unless it has page budget left.
2. If the careers page lives on another domain (e.g. acme-careers.com), that link is followed. If the site links no careers page at all, the two conventional paths /careers and /jobs are tried.
3. Every page is checked for a link to a job board (applicant tracking system). When the provider publishes an open job-board feed (the same data its own careers page shows to every visitor), all jobs are read from it.
4. Without a readable job board, the jobs come from the careers page itself: schema.org JobPosting data (what Google for Jobs reads), then links that look like individual job ads. A careers page that says "no open positions" makes the row is_hiring: false.
5. Every job gets a function and a seniority level, and the row gets its counts, signals and score.

You can also paste a job board URL directly (https://jobs.lever.co/acme, https://boards.greenhouse.io/acme): it is read without crawling a website.

What the Actor does NOT do

• It does not log in anywhere and it does not solve or bypass CAPTCHAs.
• It respects robots.txt, on the company website and on the job board provider's API. A website that disallows crawling is reported as robots_blocked and is not charged; a job board whose API disallows crawlers (SmartRecruiters, for example) is reported with its URL but not read.
• It does not use LinkedIn, Indeed or other job portals. Only the company's own website and its own job board are read.
• It does not guess. A careers page that shows its jobs only after JavaScript runs (Workday and some custom sites) gives hiring_status: "unknown" with the board's URL, never an invented number.

Input

The simplest input is a list of websites:

{
  "websites": ["https://www.figma.com", "monzo.com", "https://jobs.lever.co/acme"],
  "jobTitleKeywords": ["sales", "salesforce"]
}

Or point the Actor at a dataset, for example the output of a Google Maps Scraper run:

{
  "datasetId": "YOUR_DATASET_ID",
  "includeJobs": false
}

The website field is detected automatically (website, url, domain, companyWebsite, …) or you can name it in Website field in the dataset. A Google Maps listing link is never taken for the website; items without a website are skipped. Fields such as title, placeId, address, city and countryCode are copied into source_item, so you can join the results back to your list.

Field	What it does
websites	Company websites or job board URLs, one per line
datasetId, datasetUrlField	Import websites from a dataset
jobTitleKeywords	Words counted in job titles and departments (keyword_matches, keyword_match signal)
includeJobs	Return the job list (on by default); off gives a compact row with counts and signals only
maxJobsPerCompany	Caps the job list in a row (default 100); counts and signals always cover all jobs
maxPagesPerWebsite	Pages read on the company website to find the careers page (default 4)
maxConcurrency	Companies checked in parallel (default 20)
proxyConfiguration	Optional proxy for the company websites

Output

One row per company. Example (shortened):

{
  "input_url": "https://www.acme-software.co.uk/",
  "domain": "acme-software.co.uk",
  "status": "ok",
  "company_name": "Acme Software",
  "is_hiring": true,
  "hiring_status": "hiring",
  "careers_url": "https://www.acme-software.co.uk/careers",
  "ats_provider": "Greenhouse",
  "ats_board_url": "https://job-boards.greenhouse.io/acmesoftware",
  "jobs_source": "ats_api",
  "open_jobs_count": 3,
  "jobs_posted_last_30_days": 2,
  "newest_job_posted_at": "2026-09-25T10:00:00.000Z",
  "job_functions": { "sales": 2, "engineering": 1 },
  "seniority_levels": { "director": 1, "mid": 1, "senior": 1 },
  "leadership_roles_open": 1,
  "remote_jobs": 1,
  "hiring_countries": [],
  "top_locations": [{ "location": "London", "jobs": 1 }],
  "keyword_matches": { "sales": 2 },
  "signals": ["hiring", "hiring_sales", "hiring_engineering", "hiring_leadership", "remote_roles", "keyword_match"],
  "hiring_score": 62,
  "jobs": [
    {
      "title": "Head of Sales, EMEA",
      "department": "Sales",
      "location": "London",
      "remote": null,
      "posted_at": "2026-09-25T10:00:00.000Z",
      "url": "https://job-boards.greenhouse.io/acmesoftware/jobs/1",
      "function": "sales",
      "seniority": "director"
    }
  ],
  "source_item": null,
  "scraped_at": "2026-10-01T00:00:00.000Z"
}

Hiring status

hiring_status	is_hiring	Meaning
hiring	true	At least one open job was found
not_hiring	false	The job board was read and is empty, or the careers page says there are no openings
unknown	null	A careers page or job board exists, but its jobs could not be read (JavaScript-only board, or a provider without an open feed)
no_careers_page_found	null	The website links no careers page and has none at /careers or /jobs

jobs_source tells you where the jobs came from: ats_api (the job board's feed, complete), structured_data (schema.org on the careers page) or careers_page (job ad links on the careers page).

Signals and score

Signal	When
hiring	at least one open job
hiring_<function>	a job in that function: sales, marketing, engineering, data, customer_success, finance, hr, operations, it, product, design, legal
hiring_leadership	a director, VP or C-level role is open
high_volume_hiring	10 or more open jobs
recent_postings	3 or more jobs posted in the last 30 days
remote_roles	at least one remote job
multi_country_hiring	jobs in two or more countries
keyword_match	one of your keywords appears in a job title or department

hiring_score (0–100) is the sum of four parts, all computed from the jobs in the same row so you can check it:

• volume: 15 × log2(1 + open jobs), at most 45 (1 job = 15, 7 jobs = 45)
• freshness: 6 per job posted in the last 30 days, at most 30
• leadership: 15 if a director, VP or C-level role is open
• breadth: 2.5 per distinct job function, at most 10

Status values

status	Meaning	Charged
ok	The website (or job board) was read	yes
robots_blocked	The site's robots.txt disallows crawling	no
blocked	The site refuses automated requests (HTTP 401/403/429)	no
not_a_company_website	A social profile, directory or marketplace page, not the company's own site	no
unreachable / http_error / not_html / invalid_url / error	The website could not be read	no

Pricing

This Actor uses pay per event pricing: you pay for results, not for compute time.

• Company checked: charged once per company whose website or job board answered (status: ok), whatever the result.
• Hiring company found: charged once per company that is hiring (is_hiring: true), whatever the number of jobs.

Websites that could not be read are listed with the reason, free of charge. The job list never changes the price. The current prices are on the Pricing tab.

The Actor respects your maximum cost per run: when the limit is reached it stops before starting another company, and it never returns hiring details it could not charge for.

Use it with other Actors

• Google Maps Scraper → Company Hiring Signals: find the businesses in a niche and area, then see which of them are hiring. Start this Actor with the Maps run's datasetId.
• Website Contacts Scraper + Company Hiring Signals: run both on the same dataset and join on input_url or source_item.placeId: the hiring companies, with their phone numbers, emails and decision makers.

You can chain the runs automatically with an Apify integration (start this Actor when the previous run succeeds).

Where your list can come from

• Google Maps Scraper: set datasetId to its run's dataset. This Actor never searches Google Maps itself; it works on the dataset you bring.
• A CSV file or spreadsheet: paste the website column into websites, one per line.
• Your CRM: export the accounts and paste the website column, or push the rows into an Apify dataset with the API and set datasetId to it. datasetUrlField names the column when it is not one of the usual names.
• Make, n8n, Zapier or Clay: start the Actor through the Apify API (Apify also offers ready-made modules for some of these tools), pass websites in the input and read the run's dataset as the output.

Tips

• Large lists: 1,000 companies take a few minutes. Turn off includeJobs if you only need the signals; the rows get much smaller.
• Repeat runs (weekly, monthly) on the same list show who started hiring: compare open_jobs_count and newest_job_posted_at between runs, or schedule the Actor and send the rows with recent_postings to your CRM.
• Blocked websites: if many of your websites end as blocked, try a proxy in the input. Job board feeds never need one.
• Resuming: if a run is migrated by the platform, it continues where it stopped without checking or charging the finished companies again.

Is it legal?

The Actor reads only pages and job board feeds that companies publish openly for job seekers, respects robots.txt and does not bypass any login or CAPTCHA. Job postings are company information, not personal data. You are responsible for how you use the results, including the terms of the websites you process and the rules for B2B outreach in your country.

Limitations

• Careers pages and job boards that render their jobs only with JavaScript (Workday, some custom careers sites) give unknown with the board's URL.
• Job function and seniority are assigned from the job title (and department) with multilingual keyword rules. Unusual titles fall into other / mid.
• The job list on a careers page without a job board feed or structured data is recognised from link text and may miss jobs listed in an unusual layout.

Feedback

Found a company where the result is wrong or incomplete? Open an issue on the Issues tab with the URL. Real examples are the fastest way to improve detection.

Need it done for you?

Want this connected to your CRM or workflow, or adapted to your market? Tribloc, the team behind this Actor, builds these setups. Get in touch at tribloc.co.uk.