Hiring.Cafe Scraper — 2.8M AI-Enriched Jobs from 46 ATS

What does Hiring.Cafe Job Scraper do?

Hiring.Cafe Job Scraper extracts structured job data from hiring.cafe — including salary data, contact details, company metadata, full descriptions, and location data. It supports keyword search, location filters, and controllable result limits, so you can run the same query consistently over time. The actor also offers detail enrichment (full descriptions and company metadata) where the source provides them.

Key features

• Incremental mode — recurring runs emit and charge only for listings that are new or whose tracked content changed. First run builds the baseline state; subsequent runs emit only new or changed records.
• Detail enrichment — full descriptions and company metadata where the source provides them.
• Compact mode — AI-agent and MCP-friendly payloads with core fields only.

What data can you extract from hiring.cafe?

Each result includes Core listing fields (jobId, title, location, workplaceType, commitment, seniorityLevel, jobCategory, and salaryMin, and more), detail fields when enrichment is enabled (roleType, roleActivities, and description), contact and apply information (applyUrl), and company metadata (company, positionEmployerType, companyName, and companyWebsite). In standard mode, all fields are always present — unavailable data points are returned as null, never omitted. In compact mode, only core fields are returned.

Enable detail enrichment in the input to get richer fields such as full descriptions and company metadata where the source provides them.

Input

The main inputs are a search keyword, an optional location filter, and a result limit. Additional filters and options are available in the input schema.

Key parameters:

• query — Job search keywords.
• country — Which market to search. (default: "US")
• location — City, state, or region.
• maxResults — Maximum total results (0 = unlimited). Memory scales automatically: 256 MB up to 1000, 512 MB up to 2000, 1024 MB above. (default: 25)
• includeDetails — Fetch full job details. (default: true)
• descriptionMaxLength — Truncate description to N chars. 0 = no truncation. (default: 0)
• compact — Core fields only (for AI-agent/MCP workflows). (default: false)
• incrementalMode — Compare against previous run state. (default: false)
• stateKey — Stable identifier for tracked universe.
• skipReposts — In incremental mode, skip jobs that appear to be reposts of previously-seen expired jobs (same content hash). (default: false)

Input examples

Basic search — Keyword-driven search with a result cap.

→ Full payload per result — all standard fields populated where the source provides them.

{
  "query": "software engineer",
  "maxResults": 50
}

Incremental tracking — Only emit jobs that changed since the previous run with this stateKey.

→ First run builds the baseline state. Subsequent runs emit only records that are new or whose tracked content changed. Set emitUnchanged: true to include unchanged records as well.

{
  "query": "software engineer",
  "maxResults": 200,
  "incrementalMode": true,
  "stateKey": "software-engineer-tracker"
}

Compact output for AI agents — Return only core fields for AI-agent and MCP workflows.

→ Small payload with the most important fields — ideal for piping into LLMs without token overhead.

{
  "query": "software engineer",
  "maxResults": 50,
  "compact": true
}

Output

Each run produces a dataset of structured job records. Results can be downloaded as JSON, CSV, or Excel from the Dataset tab in Apify Console.

Example job record

{
  "jobId": "ef0d6041374f0ea3b7136b71a69ad6277a13df47bb504ac39e3d819745a1ad3f",
  "title": "Software Developer",
  "company": "AM Pierce & Associates",
  "location": "Patuxent River, Maryland, United States",
  "workplaceType": "Onsite",
  "commitment": "Full Time",
  "seniorityLevel": "Senior Level",
  "roleType": "Individual Contributor",
  "roleActivities": [
    "Oversee tasks",
    "Coordinate efforts",
    "Represent NAVAIR"
  ],
  "jobCategory": "Software Development",
  "description": "<p style=\"text-align: justify; line-height: normal; background: white;\"><span style=\"color: #000000;\"><strong><span style=\"font-size: 12pt; font-family: 'Verdana Pro', sans-serif;\">Who We Are:</span><...",
  "salaryMin": 108000,
  "salaryMax": 180000,
  "salaryCurrency": "USD",
  "salaryFrequency": "Yearly",
  "isCompensationTransparent": true,
  "requirementsSummary": "Senior software developer with DoD clearance, 8+ years of experience in engineering/software, plus 3+ years in acquisition software engineering; strong Interfacing and system integration skills.",
  "technicalTools": [
    "Software Development",
    "Open Architecture",
    "Systems Integration"
  ],
  "minYearsExperience": 8,
  "minManagementYears": null,
  "degreeRequirement": "Bachelors",
  "degreeFieldsOfStudy": [
    "Computer Science",
    "Software Engineering",
    "Electrical Engineering"
  ],
  "licensesOrCertifications": [
    "dod secret clearance"
  ],
  "languageRequirements": [
    "English"
  ],
  "securityClearance": "Secret",
  "driverLicenseRequired": false,
  "retirement401kMatching": true,
  "retirementPlan": true,
  "tuitionReimbursement": false,
  "generousParentalLeave": false,
  "generousPaidTimeOff": false,
  "fourDayWorkWeek": false,
  "visaSponsorship": false,
  "relocationAssistance": false,
  "fairChance": true,
  "militaryVeterans": true,
  "physicalLaborIntensity": "Low",
  "physicalPosition": "Sitting",
  "workplaceEnvironment": "Office",
  "computerUsage": "High",
  "cognitiveDemand": "High",
  "oralCommunicationLevel": "Medium",
  "overtimeRequired": false,
  "onCallRequirement": null,
  "airTravelRequirement": null,
  "landTravelRequirement": "Minimal",
  "morningShiftWork": null,
  "eveningShiftWork": null,
  "overnightWork": null,
  "weekendAvailabilityRequired": false,
  "holidayAvailabilityRequired": false,
  "positionEmployerType": "External Position",
  "workplaceCountries": [
    "US"
  ],
  "workplaceContinents": [
    "North America"
  ],
  "workplaceStates": [
    "Maryland, US"
  ],
  "workplaceCities": [
    "Patuxent River, Maryland, US"
  ],
  "workplaceCounties": [
    "Saint Marys County, Maryland, US"
  ],
  "isWorkplaceWorldwideOk": false,
  "latitude": 38.2709555,
  "longitude": -76.4369803,
  "companyName": "AM Pierce and Associates",
  "companyWebsite": "ampierce.com",
  "companySector": "Information Technology",
  "companyIndustries": [
    "Aerospace and Defense",
    "Information Technology"
  ],
  "companyActivities": [
    "Engineering",
    "Research"
  ],
  "companyTagline": "A woman-owned small business providing Engineering & Research, Cyber, C5ISR, Program & Acquisition Management services and solutions to government and industry.",
  "companyEmployeeCount": 120,
  "companyHqCountry": "US",
  "companyYearFounded": 2007,
  "companyOrganizationType": "Private",
  "companyParent": null,
  "companySubsidiaries": [
    "Applied Technologies Group"
  ],
  "companyStockExchange": null,
  "companyStockSymbol": null,
  "companyFundingType": null,
  "companyFundingYear": null,
  "companyFundingAmount": null,
  "companyFundingInvestors": null,
  "applyUrl": "https://ampierce.applicantpro.com/jobs/4034720.html",
  "portalUrl": "https://hiring.cafe/viewjob/gxxqfjhrbsdfualt",
  "sourceAts": "applicantpro",
  "postedDate": "2026-03-26T00:00:00.000Z",
  "scrapedAt": "2026-04-05T13:50:10.906Z",
  "source": "hiring.cafe",
  "changeType": null
}

Incremental fields

When incremental: true, each record also carries:

• changeType — one of NEW, UPDATED, UNCHANGED, REAPPEARED, EXPIRED.
• firstSeenAt, lastSeenAt — ISO-8601 timestamps tracking the listing across runs.
• isRepost, repostOfId, repostDetectedAt — populated when a new listing matches the tracked content of a previously expired one. Set skipReposts: true to drop detected reposts from the output.

How to scrape hiring.cafe

1. Go to Hiring.Cafe Job Scraper in Apify Console.
2. Enter a search keyword and optional location filter.
3. Set maxResults to control how many results you need.
4. Enable includeDetails if you need full descriptions, contact info, or company data.
5. Click Start and wait for the run to finish.
6. Export the dataset as JSON, CSV, or Excel.

Use cases

• Extract job data from hiring.cafe for market research and competitive analysis.
• Track salary trends across regions and categories over time.
• Monitor new and changed listings on scheduled runs without processing the full dataset every time.
• Build outreach lists using contact details and apply URLs from listings.
• Research company hiring patterns, employer profiles, and industry distribution.
• Use structured location data for regional analysis, mapping, and geo-targeting.
• Feed structured data into AI agents, MCP tools, and automated pipelines using compact mode.
• Export clean, structured data to dashboards, spreadsheets, or data warehouses.

How much does it cost to scrape hiring.cafe?

Hiring.Cafe Job Scraper uses pay-per-event pricing. You pay a small fee when the run starts and then for each result that is actually produced.

• Run start: $0.005 per run
• Per result: $0.0018 per job record

Example costs:

• 10 results: $0.02
• 100 results: $0.18
• 500 results: $0.91

Example: recurring monitoring savings

These examples compare full re-scrapes with incremental runs at different churn rates. Churn is the share of listings that are new or whose tracked content changed since the previous run. Actual churn depends on your query breadth, source activity, and polling frequency — the scenarios below are examples, not predictions.

Example setup: 100 results per run, daily polling (30 runs/month). Event-pricing examples scale linearly with result count.

Churn rate	Full re-scrape run cost	Incremental run cost	Savings vs full re-scrape	Monthly cost after baseline
5% — stable niche query	$0.18	$0.01	$0.17 (92%)	$0.42
15% — moderate broad query	$0.18	$0.03	$0.15 (83%)	$0.96
30% — high-volume aggregator	$0.18	$0.06	$0.13 (68%)	$1.77

Full re-scrape monthly cost at daily polling: $5.55. First month with incremental costs $0.59 / $1.11 / $1.90 for the 5% / 15% / 30% scenarios because the first run builds baseline state at full cost before incremental savings apply.

FAQ

How many results can I get from hiring.cafe?

The number of results depends on the search query and available listings on hiring.cafe. Use the maxResults parameter to control how many results are returned per run.

Does Hiring.Cafe Job Scraper support recurring monitoring?

Yes. Enable incremental mode to only receive new or changed listings on subsequent runs. This is ideal for scheduled monitoring where you want to track changes over time without re-processing the full dataset.

Can I integrate Hiring.Cafe Job Scraper with other apps?

Yes. Hiring.Cafe Job Scraper works with Apify's integrations to connect with tools like Zapier, Make, Google Sheets, Slack, and more. You can also use webhooks to trigger actions when a run completes.

Can I use Hiring.Cafe Job Scraper with the Apify API?

Yes. You can start runs, manage inputs, and retrieve results programmatically through the Apify API. Client libraries are available for JavaScript, Python, and other languages.

Can I use Hiring.Cafe Job Scraper through an MCP Server?

Yes. Apify provides an MCP Server that lets AI assistants and agents call this actor directly. Use compact mode and descriptionMaxLength to keep payloads manageable for LLM context windows.

Is it legal to scrape hiring.cafe?

This actor extracts publicly available data from hiring.cafe. Web scraping of public information is generally considered legal, but you should always review the target site's terms of service and ensure your use case complies with applicable laws and regulations, including GDPR where relevant.

Your feedback

If you have questions, need a feature, or found a bug, please open an issue on the actor's page in Apify Console. Your feedback helps us improve.

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