HiringCafe-Style Job Aggregator Stack

The Problem

Building a job aggregator that pulls from real employer career pages requires discovery, extraction, deduplication, and ranking. Most builders stitch 3-4 vendors and spend weeks on the data layer instead of the ranking product.

The Scavio Solution

Scavio (dorked search for discovery + /extract for career pages) + LLM for structured parsing + Postgres for dedupe/ranking. The data layer ships in a weekend; product effort goes into ranking quality.

Who It Is For

Builders shipping job-aggregator products, recruiting agencies productizing, indie hackers building HiringCafe alternatives.

Key Benefits

• Discovery + extract under one Scavio key
• Per-listing data cost ~$0.009
• TOS-safe (uses sanctioned SERP)
• LLM-flexible parsing (handles ATS variations)
• Stack cost ~$30 + LLM tokens

Python Example

import requests, os
H = {'x-api-key': os.environ['SCAVIO_API_KEY']}
DORKS = ['site:{d}/careers', 'site:jobs.lever.co/{d}', 'site:boards.greenhouse.io/{d}']

def pull(employer_domain):
    urls = []
    for tpl in DORKS:
        q = tpl.format(d=employer_domain.replace('.com',''))
        r = requests.post('https://api.scavio.dev/api/v1/search', headers=H, json={'query': q}).json()
        urls.extend(o['link'] for o in r.get('organic_results', [])[:5])
    return urls

JavaScript Example

// Same flow in TS.

Platforms Used