💼 Startup Jobs & Hiring Signals Scraper (Greenhouse, Lever & Ashby ATS)

Extract active job listings, remote work tags, department structures, direct application links, and tech stack hiring signals from high-growth tech companies using Greenhouse, Lever, and Ashby Applicant Tracking Systems (ATS).

Designed specifically for Cold Email Agencies, B2B SDRs, Technical Recruiters, Executive Search Teams, and Automated Prospecting Workflows (Clay, n8n, Make).

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🎯 Value Proposition & Who Is This For?

• Cold Email & Lead Generation Agencies: Identify buying intent. Companies hiring for "Salesforce", "Kubernetes", or "AI Engineer" roles have active budget and urgent software/service needs.
• Recruiters & Talent Acquisition: Monitor hiring requisitions across target startups without manual job board scanning.
• Clay.com, n8n & Make Automations: Seamlessly pull real-time hiring data into outbound enrichment tables and CRM webhooks.
• Competitive Intelligence: Track competitor headcount expansion, new department openings, and tech stack migrations.

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⚡ Key Features

• Zero Proxy Fees & Instant Execution: Directly queries public JSON APIs provided by Greenhouse, Lever, and Ashby with zero browser rendering overhead (<5 seconds for 50+ roles).
• Triple ATS Auto-Detection: Accepts plain company names (stripe), full board links (https://boards.greenhouse.io/stripe, https://jobs.lever.co/vercel, https://jobs.ashbyhq.com/linear), or domain names (stripe.com). Probes and routes automatically.
• Tech Stack Signal Extraction: Automatically scans job descriptions for 45+ tech keywords (Python, TypeScript, React, AWS, Kubernetes, OpenAI, LangChain, Snowflake, Salesforce, Rust, Go, Clay).
• Remote & Location Filters: Native boolean is_remote detection filtering "Remote", "Work From Home", and "Distributed" roles.
• Clean Database Schema: Clean JSON output with standard null handling for database compatibility.

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📥 Input Options

Parameter	Type	Required	Default / Prefill	Description
companies	String Array	Yes	["https://boards.greenhouse.io/stripe", "https://jobs.lever.co/vercel", "https://jobs.ashbyhq.com/linear"]	ATS slugs, full job board URLs, or company domains.
keywordFilter	String	No	""	Filter job titles by keyword (e.g., "Engineer", "Sales").
locationFilter	String	No	""	Filter by location (e.g., "Remote", "San Francisco").
maxJobsPerCompany	Integer	No	25	Maximum active job postings to extract per company.

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📤 Sample Output Preview

JSON Output

[
  {
    "company_slug": "stripe",
    "ats_platform": "Greenhouse",
    "job_title": "Software Engineer - Infrastructure",
    "department": "Engineering",
    "location": "San Francisco, CA / Remote",
    "is_remote": true,
    "employment_type": "Full-time",
    "posted_at": "2026-10-01T14:30:00.000Z",
    "apply_url": "https://boards.greenhouse.io/stripe/jobs/4567890",
    "company_jobs_url": "https://boards.greenhouse.io/stripe",
    "tech_keywords": [
      "Ruby",
      "Go",
      "AWS",
      "Kubernetes",
      "PostgreSQL"
    ]
  }
]

Table View

Company	ATS Platform	Job Title	Department	Location	Remote	Tech Stack Signals	Apply Link
stripe	Greenhouse	Software Engineer - Infrastructure	Engineering	San Francisco / Remote	true	Ruby, Go, AWS, Kubernetes	Apply Link
vercel	Lever	Senior Frontend Engineer	Product	Remote - US	true	TypeScript, Next.js, React	Apply Link
linear	Ashby	Product Designer	Design	London, UK	false	Figma, TypeScript	Apply Link

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🔄 Step-by-Step Integration Guide

1. Clay.com Integration

1. In your Clay table, add a new Enrichment Action -> select Apify.
2. Choose Run Actor and select startup-hiring-ats-scraper.
3. Pass your domain or ATS company list into companies.
4. Map the resulting dataset array directly into Clay columns to trigger automated outreach.

2. n8n & Make.com Webhooks

1. Add an Apify Node in n8n or Make.com.
2. Select Run Actor & Wait for Completion.
3. Set Actor ID to startup-hiring-ats-scraper.
4. Connect the dataset items directly to your CRM (HubSpot, Salesforce) or Slack notifications.

3. Python API Integration

from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_API_TOKEN")

run_input = {
    "companies": [
        "https://boards.greenhouse.io/stripe",
        "https://jobs.lever.co/vercel",
        "https://jobs.ashbyhq.com/linear"
    ],
    "keywordFilter": "Engineer",
    "maxJobsPerCompany": 10
}

run = client.actor("startup-hiring-ats-scraper").call(run_input=run_input)

for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(f"{item['company_slug']} ({item['ats_platform']}): {item['job_title']} -> {item['apply_url']}")

4. JavaScript / Node.js API Integration

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_APIFY_API_TOKEN' });

const run = await client.actor('startup-hiring-ats-scraper').call({
    companies: ['stripe', 'vercel', 'linear'],
    keywordFilter: 'Engineer'
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(`Extracted ${items.length} job postings:`, items);

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⚡ Speed & Performance Benchmarks

• 3 Companies (Default Run): ~3 seconds (<100ms per board API call)
• 25 Companies: ~8 seconds (concurrent probing)
• 100 Companies: ~22 seconds

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🛡️ Monetization & Support

Maintained for high-concurrency Apify workflows. For feature requests or custom B2B scraper development, contact us via Apify Console.