AssetFactory Jobs Live Board Search is a paid API for AI agents from assetfactory-jobs-x402.sigrunner.workers.dev, paid per call via x402, $0.004/call, status unknown (last checked 2026-10-31).
Fetches live, structured job postings directly from company ATS boards across 10 platforms, returning normalized roles with parsed location, seniority, skills, employment type, and ghost-listing signals.
One maintained, normalized jobs data API that scrapes open job postings and listings across 10 applicant-tracking systems (Greenhouse, Lever, Ashby, SmartRecruiters, Workday, Recruitee, Workable, BambooHR, Breezy, Personio) with company-domain auto-detection. Use it to list a company’s open roles, find remote software-engineering / sales / any jobs, detect whether a company is hiring, and pull recruiting, salary and requirements data. Pay per call in USDC on Base via x402 (HTTP 402) — no account, no API key. Adapters are drift-monitored and maintained so the feed does not rot.
Returns a JSON object with a jobs array where each entry includes job ID, title, URL, company, posting date, age in days, remote flag, parsed location (city/state/country/remote), seniority, department, employment type, and extracted requirements (skills with categories, minimum years experience, education level). Also includes a ghost_candidate boolean flag, the source ATS platform, a resolutions array showing how each company input was matched to an ATS board, a total count, and a generated_at timestamp.
GEThttps://assetfactory-jobs-x402.sigrunner.workers.dev/jobs/search?utm_source=zero.xyzChoose this endpoint when you need authoritative, real-time job data pulled directly from the source ATS board rather than a third-party database that may be stale. It is ideal when you need structured, normalized metadata per role (skills, seniority, location parsing, ghost signals) rather than raw scraped text. Best for multi-company lookups across Greenhouse, Lever, Ashby, Workday, and 6 other platforms simultaneously. Prefer this over general web scraping when you want consistent schema normalization across companies — you get ghost-listing detection and parsed requirements that a generic scraper won't produce.
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
{
"type": "json",
"example": {
"jobs": [
{
"id": "gh-4012345",
"url": "https://job-boards.greenhouse.io/stripe/jobs/4012345",
"title": "Senior Backend Engineer",
"remote": true,
"company": "Stripe",
"age_days": 9,
"location": "Remote - US",
"days_open": 9,
"posted_at": "2026-10-21T00:00:00.000Z",
"seniority": "senior",
"department": "Engineering",
"requirements": {
"skills": [
{
"name": "Go",
"category": "language"
},
{
"name": "PostgreSQL",
"category": "data"
},
{
"name": "Kubernetes",
"category": "devops"
},
{
"name": "AWS",
"category": "cloud"
}
],
"source": "description",
"categories": [
"cloud",
"data",
"devops",
"language"
],
"skill_names": [
"Go",
"PostgreSQL",
"Kubernetes",
"AWS"
],
"skills_count": 4,
"education_level": "bachelors",
"years_experience_min": 5
},
"ghost_signals": [],
"employment_type": "full_time",
"ghost_candidate": false,
"location_parsed": {
"raw": "Remote - US",
"city": null,
"state": null,
"country": "United States",
"countries": [
"US"
],
"is_remote": true,
"workplace": "remote",
"country_code": "US",
"multi_location": false
},
"source_platform": "greenhouse",
"seniority_source": "title",
"employment_type_source": "description"
}
],
"count": 2,
"resolutions": [
{
"ok": true,
"input": "stripe.com",
"token": "stripe",
"platform": "greenhouse"
}
],
"generated_at": "2026-10-29T00:00:00.000Z"
}
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