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Trace — Jobs Core API- Structured Job Posting Data Withou...
0x59 · 2026-06-17 · via Show HN

Trace Jobs Core API — Interpretation‑free job posting data, delivered without scraping.

Trace

Jobs Core API

Interpretation‑free job posting data, delivered without scraping.

View API Pricing & Access

Why this exists

  • Scraping Is Fragile: HTML layouts shift without notice, breaking pipelines and burning engineering time.
  • Extraction Is Unreliable: LLM‑based parsing introduces silent errors, hallucinated fields, and schema drift.
  • Sources Don’t Align: Job boards and ATS systems format titles, locations, and timestamps differently.
  • Everyone Rebuilds the Same Stack: Teams repeatedly write scrapers, mappers, and dedupers just to reach clean data.

What it is

The Jobs Core API provides interpretation-free job posting data: records derived deterministically from machine-readable sources, without scraping, AI extraction, enrichment, classification, or inferred metadata.

  • Data Source: 9800+ structured feeds
  • Data Refresh: Daily at 06:00 UTC
  • Ingestion Rate: 13k/day average
  • Data Standard: Schema.org
  • Deduplication: SHA-256
  • Normalization: Best‑effort ISO mapping with original values preserved when unmappable.

We ingest job data daily from public machine‑readable endpoints, translate it into a standard form, apply best‑effort ISO field normalization, canonicalize it via RFC 8785, and commit it to a content‑addressed store. Zero scraping, zero guesswork, maximum fidelity.

View sample queries & real data→

What you get

  • Months of Saved Engineering Time: Skip building scrapers and fixing broken pipelines. We handle the upstream mess so your team can focus on building your actual product.
  • Instant Market Coverage: Tap into 9800+ feeds and ~13k new postings daily. Get full market visibility overnight without the massive infrastructure and data-gathering costs.
  • Standard Data, Zero Mapping: Records are normalized to Schema.org, with original upstream values preserved when ISO mapping is ambiguous.
  • Lower Compute & Storage Costs: Automated SHA-256 byte-level deduplication ensures you only process unique, net-new data. Delivered as sparse JSON optimized for databases and AI/RAG apps.

Who it's for

  • Investment & Market Analysts: Queries and tracks specific market sectors, job titles, or regional hiring trends directly from Python/Pandas without dealing with unstructured web text.
  • AI/RAG Product Teams: Feeds structured JSON fields straight into embedding models and vector DBs. Eliminates token waste and hallucinations from unstructured HTML.
  • Niche Job Boards & Aggregators: Syncs net-new listings to Postgres or Supabase via target query cron jobs, replacing broken Puppeteer/Playwright scrapers.

Why it's different

  • Stability: Direct connections to machine‑readable feeds eliminate breakage from frontend redesigns.
  • Predictability: No scraping or AI parsing means zero structural drift and fully deterministic fields.
  • Compliance: Built exclusively on public machine endpoints intended for automated access, minimizing legal risk.
  • Readiness: Native Schema.org JSON with best-effort ISO-standardized fields, preserving originals when mapping is ambiguous.

Give it a try

Paste the command below to receive real, fresh, data right to your terminal.

Note: This sandbox key has limited search/filter access. Sign up for a full API key.

Recent Postings in Major Tech Hubs

$ curl -G \
   -H "X-API-Key: THIS_IS_A_SANDBOX" \
   --data-urlencode "city=san francisco" \
   --data-urlencode "city=new york" \
   --data-urlencode "city=austin" \
   --data-urlencode "city=seattle" \
   --data-urlencode "sortby=date_posted" \
   "https://api.kaleh.net/trace/jobs/core/search"

Read the full API reference →


Pricing

Basic

$0/mo

200 requests / month
(Up to 2.4k records)

Get Basic

$25/mo

10,000 req / month
(Up to 120k records)

Get Pro

Team

$50/mo

25,000 req / month
(Up to 300k records)

Get Team

Scale

$100/mo

55,000 req / month
(Up to 660k records)

Get Scale

Are you an enterprise user? Do you need historical archive access or bulk data? Let's talk


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