Career Page Job Scraper & Change Monitor

What this Actor does

Monitor public company career pages and extract structured job openings for recruiting and hiring intelligence.

It processes user-provided public URLs, prioritizes JSON-LD/schema.org JobPosting structured data, and can optionally use a conservative fallback for visible public job-card links on career pages. It normalizes useful fields, deduplicates rows, and saves structured records to the Apify dataset.

Why this Actor is useful

Teams pay for this kind of extraction when it saves manual research, creates repeatable monitoring, feeds spreadsheets or CRMs, and turns public pages into clean API-ready datasets.

Who this is for

• Recruiters
• Staffing agencies
• Job boards
• HR tech founders
• Hiring intelligence teams
• Career newsletter operators
• B2B sales teams targeting hiring companies

Common use cases

• Track new openings across target companies
• Feed job boards or hiring newsletters
• Find companies currently hiring for B2B sales outreach
• Monitor competitor hiring signals
• Build recurring hiring intelligence datasets

Input

• startUrls: Public URLs to extract from. Use only pages you are allowed to access without login or bypassing access controls.
• maxItems: Maximum number of rows to save.
• maxConcurrency: Number of pages processed in parallel. The default is intentionally conservative.
• extractionMode: Use structuredDataOnly or structuredDataWithFallback. The default enables the safe public job-card fallback.
• includeDescription: Include public job descriptions from JobPosting structured data when available.
• includeRawStructuredData: Adds the original JSON-LD object for audit/debugging.
• requestTimeoutSecs: Maximum time to spend on a single page.
• proxyConfiguration: Optional Apify proxy configuration where permitted by your source review.

Output

• companyName: Hiring company name when exposed in structured data.
• careerPageUrl: The career page or job page supplied or discovered as the source.
• jobTitle: Public job title.
• jobUrl: Public application or job detail URL.
• location: Job location as listed by the source.
• department: Department or team when available.
• employmentType: Employment type such as full-time, contract, or internship.
• remoteStatus: Remote or hybrid signal when available.
• postedDate: Posting date or valid-through date when available.
• detectedAt: Timestamp when this Actor extracted the row.
• sourceUrl: URL where the data was extracted.
• extractionMethod: structured_data for valid JobPosting schema, or fallback_public_job_card for visible public career-page job cards.
• confidenceScore: Heuristic confidence score based on structured data availability.
• missingFields: Output fields that were not available from the source page.

Sample input

{
  "startUrls": [
    {
      "url": "https://job-boards.greenhouse.io/stripe"
    }
  ],
  "maxItems": 25,
  "maxConcurrency": 3,
  "extractionMode": "structuredDataWithFallback",
  "includeDescription": false,
  "requestTimeoutSecs": 30,
  "includeRawStructuredData": false
}

Sample output

{
  "companyName": "Example Robotics Labs",
  "careerPageUrl": "https://example.com/",
  "jobTitle": "Senior Backend Engineer",
  "jobUrl": "https://example.com/company-careers/senior-backend-engineer",
  "location": "Austin, TX, US",
  "department": "Engineering",
  "employmentType": "FULL_TIME",
  "remoteStatus": "HYBRID",
  "postedDate": "2026-06-01",
  "detectedAt": "2026-06-12T00:00:00.000Z",
  "sourceUrl": "https://example.com/",
  "extractionMethod": "structured_data",
  "confidenceScore": 0.95,
  "missingFields": []
}

How to use

Run this Actor on Apify with public URLs, export the dataset as JSON, CSV, Excel, or through the Apify API, then connect the output to Google Sheets, Make, Zapier, a webhook, your CRM, or an internal dashboard. For monitoring, save the input as an Apify task and schedule recurring runs.

Best practices

• Start with a small set of reviewed public URLs.
• Prefer pages with schema.org JSON-LD structured data.
• Use structuredDataOnly when you want the highest precision and can tolerate empty output.
• Use structuredDataWithFallback when reviewed public career pages show visible job cards but no JobPosting schema.
• Keep maxConcurrency low for smaller websites.
• Review source website rules before scheduling recurring runs.
• Keep includeRawStructuredData off unless you need audit details.

Compliance and responsible use

This Actor is for public data only. It must not be used to bypass logins, paywalls, CAPTCHAs, or security systems, collect private data, gather sensitive personal data, or support spam or abuse. You are responsible for following applicable laws and source website rules.

Limitations

• Output quality depends on public structured data available on the source pages.
• Fallback extraction is intentionally conservative and only looks for visible public job-card/link patterns. It does not claim universal career page support.
• Some fields may be empty when the source does not publish them.
• The Actor does not claim support for any specific third-party platform.
• Website markup and access policies can change.

Troubleshooting

• Empty output usually means the page has no public JobPosting JSON-LD/schema.org data.
• Invalid URL errors mean one or more input URLs are malformed.
• Slow runs can usually be improved by lowering maxConcurrency.
• Missing fields are source-data limitations, not inferred values.

Changelog

• v0.2.0: Production-readiness pass with improved positioning, samples, schema descriptions, and responsible-use notes.

How much does Career Page Job Scraper & Change Monitor cost?

This Actor uses pay-per-event pricing: you pay only for what it delivers, and platform usage is included.

Event	Price
Actor start	$0.01 per run
Result scraped	$0.005 each ($5.00 per 1,000)

Set Maximum cost per run in the run options to cap your spend; the Actor stops when the limit is reached. Check the Pricing tab for current prices and plan discounts.

Use Career Page Job Scraper & Change Monitor with AI agents (MCP)

Give Claude, ChatGPT, Cursor, VS Code or any MCP client this Actor as a tool through the hosted Apify MCP server. The agent sees the input fields with descriptions and example values, runs the Actor, and reads the results.

MCP server URL (this Actor only):

https://mcp.apify.com/?tools=technicaldost/company-career-page-monitor

Claude Code:

$claude mcp add --transport http apify "https://mcp.apify.com/?tools=technicaldost/company-career-page-monitor" --header "Authorization: Bearer YOUR_APIFY_TOKEN"

Cursor, VS Code, Claude Desktop and other clients (mcp.json or the client's MCP settings):

{
  "mcpServers": {
    "apify": {
      "url": "https://mcp.apify.com/?tools=technicaldost/company-career-page-monitor",
      "headers": { "Authorization": "Bearer YOUR_APIFY_TOKEN" }
    }
  }
}

Clients that support sign-in (such as Claude.ai connectors) can use the URL without a token and log in to Apify instead. Get your token in Apify Console → Settings → API & Integrations, or generate a ready config for your client at mcp.apify.com. In the agent the tool is named technicaldost--company-career-page-monitor; ask it, for example, to "run Career Page Job Scraper & Change Monitor with {"startUrls": [{"url": "https://job-boards.greenhouse.io/stripe"}], "maxItems": 20}".

AI agents without an Apify account can also run and pay for this Actor per request with x402 agentic payments.

Run Career Page Job Scraper & Change Monitor via API

Run the Actor and get its results in one call (replace YOUR_APIFY_TOKEN):

curl -X POST "https://api.apify.com/v2/acts/technicaldost~company-career-page-monitor/run-sync-get-dataset-items?token=YOUR_APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"startUrls": [{"url": "https://job-boards.greenhouse.io/stripe"}], "maxItems": 20}'

Python (pip install apify-client):

from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")
run = client.actor("technicaldost/company-career-page-monitor").call(run_input={"startUrls": [{"url": "https://job-boards.greenhouse.io/stripe"}], "maxItems": 20})
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

JavaScript / TypeScript (npm install apify-client):

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_APIFY_TOKEN' });
const run = await client.actor('technicaldost/company-career-page-monitor').call({"startUrls": [{"url": "https://job-boards.greenhouse.io/stripe"}], "maxItems": 20});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

Long runs: start them with POST /v2/acts/technicaldost~company-career-page-monitor/runs and fetch the dataset when the run finishes, or receive a webhook.

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FAQ

Can I use Career Page Job Scraper & Change Monitor with AI agents like Claude or ChatGPT?

Yes. Connect the Apify MCP server with ?tools=technicaldost/company-career-page-monitor (see above) and the agent can run the Actor and read its results on its own.

Can I call Career Page Job Scraper & Change Monitor from my own code?

Yes. Use the REST API, or the official Python and JavaScript clients shown above. Results are available as JSON, CSV, Excel, XML or HTML.

How do I run it on a schedule?

Save your input as a task in Apify Console and add a schedule (for example, daily). Use webhooks or integrations to send each run's results onward.

Is it legal to use this Actor?

It works with publicly available data. Make sure your use complies with the source website's terms and with data protection laws such as GDPR, especially for personal data.

Something doesn't work or I need a feature. What should I do?

Open an issue in the Issues tab on this Actor's page with an example input, and we'll look into it.