Djinni.co Jobs Scraper — Remote Tech Jobs

Scrape public Djinni.co job listings by keyword, country, city, or saved search URL and return one structured dataset record per unique job. Use it for recruiting, labor-market research, salary analysis, and job-board monitoring.

The Actor supports keyword searches, country/city filters, exact public Djinni search URLs, pagination, optional detail-page enrichment, and additional current Djinni query parameters through filters.

Output

Each job includes its ID, title, canonical URL, company, location, remote indicator, employment type, experience, English level, category, salary text and parsed bounds when available, description, publication time, search query, scrape time, and record status. Missing values remain null; compensation is never inferred.

Field group	Examples
Identity	jobId, title, jobUrl, searchQuery
Employer	company, companyUrl, category
Role	location, remote, employmentType, experience, englishLevel
Compensation	salary, salaryMin, salaryMax when Djinni discloses it
Content	description, publishedAt, scrapedAt, status

Example input

{
  "searchQueries": ["software engineer", "data analyst"],
  "countries": ["Ukraine", "Poland"],
  "maxResults": 50,
  "includeDetails": true
}

For exact Djinni advanced-search filters, pass a public search URL in startUrls, or use filters, for example { "employment": "remote", "exp_level": "3y" }. The public search page can change its filter vocabulary; startUrls is the most stable option for a saved search.

Pricing

The Actor uses pay per event. The primary event is $0.002 per unique job record written; a small automatic start event also applies. A run that is blocked or returns no matching public jobs writes no result records and incurs no result-item events.

Examples: an empty run costs only the automatic start event; a one-job run is approximately $0.00205 before platform compute; a 100-job run is approximately $0.20005 before platform compute.

Responsible use

This Actor accesses only public Djinni.co pages. Use it in compliance with Djinni’s terms, robots guidance, applicable law, and data-protection obligations. It does not log in, access private candidate data, bypass CAPTCHAs, or defeat access controls. If Djinni returns a challenge or empty response, the run records a truthful diagnostic in SUMMARY.

Use cases

• Build public prospect lists and qualify organizations or professionals before responsible outreach.
• Run a one-off research job and export the structured result as JSON, CSV, Excel, XML, or RSS from Apify.
• Schedule the same input to monitor changes over time and send completed datasets to a webhook or integration.
• Feed schema-shaped records into a database, spreadsheet, BI tool, or AI workflow with the source URL retained for verification.

Run Djinni.co Jobs Scraper — Remote Tech Jobs with the Apify API

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('muhammadafzal/djinni-co-jobs-scraper').call({
  "searchQueries": [
    "software engineer"
  ],
  "anyWords": "",
  "excludeWords": "",
  "countries": [],
  "cities": [],
  "startUrls": [],
  "filters": {},
  "maxResults": 20
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

You can also run the Actor from Apify Console, schedules, webhooks, the REST API, Make, Zapier, n8n, or the hosted Apify MCP server.

Frequently asked questions

Can I schedule Djinni.co Jobs Scraper — Remote Tech Jobs?

Yes. Use an Apify schedule to run the same saved input at a chosen interval, then connect a webhook or integration to process the dataset when the run finishes.

How should I test a new input?

Begin with the prefilled example or a small limit. Confirm that the output fields, source coverage, runtime, and live charges match your workflow before increasing the scope.

How do I export the results?

Open the run's default dataset in Apify Console and export JSON, CSV, Excel, XML, or RSS. Applications can retrieve the same records through the Apify API client or REST dataset endpoint.

Can an AI agent call this Actor?

Yes. Add muhammadafzal/djinni-co-jobs-scraper through the hosted Apify MCP server or call it through the API. The Actor's input and dataset schemas help agents construct valid requests and interpret returned records.

Recommended workflow

1. Define the smallest useful scope. Choose a representative public URL, query, identifier, or filter and keep the first result limit low.
2. Run and inspect. Check the run log, dataset item count, field coverage, source URLs, and live event or usage charges.
3. Validate downstream assumptions. Confirm nullable fields, deduplication keys, timestamps, and any locale-specific formats before importing records into another system.
4. Scale gradually. Increase limits or scheduling frequency only after the small run behaves as expected. Use Apify's maximum-cost and timeout controls to bound large jobs.
5. Monitor changes. Keep a small known-good input as a canary. If the source layout or API changes, compare the new dataset with a previously validated run and report the run ID when requesting support.

For recurring workflows, store the exact Actor input with your pipeline configuration. This makes runs reproducible and helps distinguish a source-data change from an input change.