LinkedIn New Jobs Monitor

Monitor public LinkedIn job searches without login. Emit evidence-backed new-posting events only after a free baseline. Built for recruiters, job boards, sales teams, market researchers, and labor-market platforms.

Start in 30 seconds

{
  "queries": [
    "AI engineer"
  ],
  "locations": [
    "United States"
  ],
  "monitorKey": "ai-engineer-us",
  "maxResultsPerSearch": 10,
  "maxEvents": 25
}

Run the example, inspect the Dataset, and save recurring inputs as Apify Tasks. Export JSON, CSV, Excel, API output, or webhook payloads.

Choose this Actor when

Use this Actor when you need a repeatable event, comparison, or direct-evidence workflow. For a one-off unfiltered export use LinkedIn Jobs Search Scraper. For complete records from known IDs or URLs use LinkedIn Job Details Scraper.

Run a bounded starter Task

Open the workflow-specific starter Task to inspect a small, editable input before running. Keep the first run bounded, then review the evidence fields and RUN_SUMMARY before increasing limits or scheduling it.

Current LinkedIn search behavior

No LinkedIn account or cookies are required. The Actor uses public guest job-search and job-detail pages. LinkedIn controls search ranking and may interpret query wording, so monitors compare stable job IDs within repeated bounded searches rather than claiming complete market coverage. Analyses and events are emitted only when direct public evidence satisfies the documented rule.

For recurring use, keep the same query, location, and monitor key. Prefer small daily checks over occasional deep searches so baseline and change semantics remain auditable.

First run checklist

1. Run the bounded example input and inspect the Dataset plus RUN_SUMMARY.
2. For monitors, confirm the first run creates a free baseline and emits no paid event.
3. Re-run the same Task once to confirm unchanged checks remain free.
4. Add a schedule or webhook only after the event evidence and stable keys match your workflow.

What you get

• Direct public LinkedIn job URLs and evidence fields
• Stable job IDs, deterministic event or analysis hashes, and explicit caveats
• Pure-HTTP 256 MB execution with bounded retries and safe limits
• No login, cookies, profiles, employees, emails, or private data

Pricing and billing

Launch PPE price: $20.00 per 1,000 direct newly posted job events, or $2.00 for 100. The first run creates a free baseline. Unchanged checks emit zero paid rows, and safety-cap failures do not update state.

The first run is a free baseline. Later rows require an unseen job ID and a disclosed posting date later than the previous completed check date. Newly surfaced older or same-day ambiguous cards are free. Diagnostics, duplicates, incomplete fetches, baselines, unchanged checks, and unsupported inferences are never billed.

Output schema

Every billable row exposes direct source evidence and the fields documented in the Dataset schema. Error-only or placeholder rows are never written.

The separate RUN_SUMMARY record reports scanned jobs, saved rows or events, baseline/unchanged state, and failed requests. It is diagnostic and never billed.

Automation and AI agents

Use Apify Tasks and schedules, webhooks, ChatGPT, Claude, Neuton Actors MCP, n8n, Make, Zapier, Clay, a CRM, warehouse, RAG pipeline, or agent workflow.

Hosted Apify MCP endpoint: https://mcp.apify.com/?tools=neuton/linkedin-new-jobs-monitor

Explore the LinkedIn data family

• LinkedIn Jobs Search Scraper for broad public-job discovery
• LinkedIn Job Details Scraper for complete records from job IDs or URLs
• LinkedIn Company Hiring Signals for evidence-backed company aggregates
• LinkedIn Salary Jobs Intelligence for compensation-bearing postings

SEO keywords

LinkedIn jobs monitor, LinkedIn job changes, LinkedIn benefits data, talent demand benchmark, visa sponsorship jobs, cross-border hiring intelligence, recruiting intelligence API, Apify LinkedIn Actor.

Responsible use

Process public job-posting evidence for legitimate recruiting, workforce, compensation, mobility, compliance, and market research. Do not scrape private profiles, bypass access controls, spam people, infer protected traits, or automate unlawful employment decisions. Review LinkedIn's current terms and applicable privacy and employment laws before production use.