LinkedIn New Job Posting Monitor and Alerts

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Monitor new public LinkedIn jobs without paying for duplicates

LinkedIn New Job Posting Monitor and Alerts turns repeatable public job searches into a deduplicated alert feed. Configure one or more keyword and location searches, schedule the Actor, and receive only postings that the same monitor has not delivered before. It is designed for recruiting pipelines, personal job alerts, niche job boards, labor-market research, and automation workflows that need new records rather than the same search results on every run.

The Actor reads LinkedIn public guest job-search pages. It requires no LinkedIn login, cookies, account credentials, profile access, or personal-data scraping. Returned records contain public job-card fields such as job ID, title, company, location, posting time, canonical job URL, and the search that found the posting.

Persistent monitoring

Set monitorId to a stable name and run the Actor on a schedule. A named key-value store retains a bounded list of previously delivered public job IDs. Repeated results are suppressed, while genuinely new IDs become alerts. Different monitor IDs keep independent histories, so a remote Python search can run alongside a local data-engineering search without mixing state.

previewOnly=true is the default. Preview mode fetches live public results and reports source health without charging custom events or changing deduplication state. After validating the query, switch preview off for scheduled monitoring. The Actor uses limited-permission storage access and does not request broad account permissions.

Search controls

Each run accepts up to 20 keyword and location searches. Filters include posts from the past day, week, or month and a remote-only option. Runtime and output are bounded by maxResults and maxAlerts, with hard limits of 500. If one query fails while another succeeds, successful results are returned with explicit partial-source diagnostics. If every public query fails, the run fails visibly instead of silently returning an empty result.

Pricing

The pricing model is Pay per event + usage. There is no start fee. Each newly delivered posting charges the custom event new_linkedin_job_alert at $0.001. Duplicate postings are not charged as new alerts. Apify platform usage is charged separately to the runner under the platform's normal compute and storage rules. Preview mode does not emit the paid custom event.

Output and scheduling

Use the alerts dataset view for a compact table of posting time, title, company, location, URL, keywords, and job ID. The run summary records fetched jobs, new jobs, suppressed duplicates, and per-search source status. For continuous monitoring, create an Apify schedule with the same monitorId; the first paid run establishes state and later runs emit only unseen postings.

Public endpoints can change without notice. This Actor reports source failures, limits request volume, stores only bounded deduplication state, and is intended for lawful use of public information. Users remain responsible for complying with applicable terms, laws, and internal data policies.