# Startup Jobs & Hiring Signals Scraper (Greenhouse & Lever ATS) (`abhay512/startup-hiring-ats-scraper`) Actor

Extract active job postings, remote roles, tech stack signals & apply links from funded startups on Greenhouse & Lever. Built for Clay, n8n & B2B recruiting.

- **URL**: https://apify.com/abhay512/startup-hiring-ats-scraper.md
- **Developed by:** [Bad Devil](https://apify.com/abhay512) (community)
- **Stats:** 2 total users, 1 monthly users, 0.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $2.50 / 1,000 results

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## 🚀 Startup Jobs & Hiring Signals Scraper (Greenhouse & Lever ATS)

Extract active job postings, remote role indicators, tech stack signals, and direct apply links from top venture-backed startups and high-growth companies using **Greenhouse** and **Lever** Applicant Tracking Systems (ATS).

Built for **Clay.com**, **n8n**, **Make.com**, **B2B lead generation agencies**, and **technical recruiters**.

***

### ⚡ Why Use This Scraper?

- **Zero Proxy Costs & No Cloudflare Blocks**: Directly queries public JSON REST endpoints provided by Greenhouse and Lever with zero headless browser overhead.
- **Dual ATS Auto-Detection**: Pass company names (`stripe`), full board URLs (`https://boards.greenhouse.io/stripe`), or domain names (`stripe.com`). The scraper automatically probes and routes requests to the correct ATS API.
- **Tech Stack Signal Extraction**: Automatically scans job descriptions for 35+ engineering and B2B software signatures including `Python`, `TypeScript`, `React`, `AWS`, `Kubernetes`, `OpenAI`, `LangChain`, `Snowflake`, `HubSpot`, `Salesforce`, `Rust`, `Go`, and more.
- **Remote & Location Intelligence**: Built-in boolean remote flag (`is_remote`) that detects `"Remote"`, `"Work From Home"`, `"Anywhere"`, and `"Distributed"` tags across title and location fields.
- **Clean JSON Output for Webhooks & DBs**: Every job record includes normalized timestamps, apply links, department names, and employment types (`Full-time`, `Contract`, etc.).

***

### 🎯 Primary Use Cases

1. **B2B Outbound & Lead Intent Scoring**: Find venture-backed companies actively hiring for roles in your niche (e.g. "DevOps", "Salesforce Administrator", "AI Engineer") to identify active spending budget.
2. **Clay.com & n8n Automation Pipelines**: Extract hiring signals and pair them with our **B2B Website Contact & Tech Stack Enricher** (`b2b-lead-tech-enricher`) to locate decision-maker contacts (CTO, VP of Sales) and initiate targeted cold email campaigns.
3. **Technical Recruiting & Executive Search**: Source real-time hiring requisitions across hundreds of high-growth tech companies without manual board checking.
4. **Competitive Intelligence**: Monitor tech stack shifts and hiring trends across competitors or portfolio companies.

***

### 📥 Input Parameters

| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
| `companies` | Array of Strings | Yes | `["stripe", "vercel", "anthropic", "figma", "linear", "retool", "scaleai", "mercury"]` | Company slugs, full ATS board URLs, or company domain names. |
| `keywordFilter` | String | No | `""` | Filter job titles by keyword (case-insensitive, comma-separated e.g. `"AI, Engineer"`). |
| `locationFilter` | String | No | `""` | Filter by job location (case-insensitive e.g. `"Remote"`, `"San Francisco"`, `"US"`). |
| `maxJobsPerCompany` | Integer | No | `25` | Maximum active job postings to extract per company (Min: 1, Max: 500). |

#### Example Input (`input.json`)

```json
{
  "companies": [
    "stripe",
    "https://jobs.lever.co/vercel",
    "anthropic.com",
    "figma"
  ],
  "keywordFilter": "Engineer",
  "locationFilter": "Remote",
  "maxJobsPerCompany": 15
}
```

***

### 📤 Output Dataset Schema

Each job record pushed to the default dataset contains the following clean fields:

```json
{
  "company_slug": "vercel",
  "ats_platform": "Lever",
  "job_title": "Senior AI Infrastructure Engineer",
  "department": "Engineering",
  "location": "San Francisco, CA / Remote",
  "is_remote": true,
  "employment_type": "Full-time",
  "posted_at": "2026-10-01T14:30:00+00:00",
  "apply_url": "https://jobs.lever.co/vercel/a1b2c3d4-5678-90ef/apply",
  "company_jobs_url": "https://jobs.lever.co/vercel",
  "tech_keywords": [
    "Python",
    "TypeScript",
    "Next.js",
    "AWS",
    "Kubernetes",
    "OpenAI"
  ]
}
```

> **Note**: For any missing or unavailable URLs, the fields return JSON `null` (not empty strings) to comply with database strict schemas.

***

### 🔗 Combining with B2B Contact & Tech Enricher for Automated Lead Gen

Achieve 10x response rates by triggering personalized outreach based on real-time hiring intent:

```mermaid
flowchart LR
    A["1. Startup ATS Scraper (This Actor)"] -->|Extract Hiring Companies & Stack Signals| B["2. Clay.com / n8n / Make Pipeline"]
    B -->|Enrich Domain & Contacts| C["3. B2B Contact & Tech Enricher (b2b-lead-tech-enricher)"]
    C -->|Verified Emails + Socials| D["4. Automated Cold Outreach (Instantly / Smartlead)"]
```

#### 3-Step Outbound Workflow:

1. **Run `startup-hiring-ats-scraper`**: Fetch active job openings and tech stack keywords (e.g., companies hiring `Salesforce` or `Kubernetes` engineers).
2. **Pass Domain to `b2b-lead-tech-enricher`**: Scraping company websites (`domain.com`) extracts business emails, contact forms, social media profiles, and website tech signatures.
3. **Launch Targeted Campaigns**: Send hyper-relevant cold emails referencing the exact open job title and technology stack extracted from their hiring board.

***

### ⚙️ Local Development & Testing

```bash
## Install dependencies
pip install -r requirements.txt

## Run locally via Apify CLI
apify run
```

***

### 🛡️ License & Support

Built & maintained for high-concurrency Apify workflows. For feature requests or custom B2B scraper development, reach out via Apify Console.

# Actor input Schema

## `companies` (type: `array`):

List of company slugs (e.g., 'stripe'), full ATS URLs ('https://boards.greenhouse.io/stripe', 'https://jobs.lever.co/vercel'), or domain names ('stripe.com').

## `keywordFilter` (type: `string`):

Optional filter for job titles (e.g., 'AI', 'Engineer', 'Sales', 'Marketing'). Case-insensitive.

## `locationFilter` (type: `string`):

Optional filter for locations (e.g., 'Remote', 'US', 'San Francisco', 'London'). Case-insensitive.

## `maxJobsPerCompany` (type: `integer`):

Maximum number of active job postings to extract per company.

## Actor input object example

```json
{
  "companies": [
    "stripe",
    "vercel",
    "anthropic",
    "figma",
    "linear",
    "retool",
    "scaleai",
    "coinbase"
  ],
  "keywordFilter": "",
  "locationFilter": "",
  "maxJobsPerCompany": 25
}
```

# Actor output Schema

## `dataset` (type: `string`):

URL to the dataset containing extracted active jobs, remote flags, and tech stack signals.

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "companies": [
        "stripe",
        "vercel",
        "anthropic",
        "figma",
        "linear",
        "retool",
        "scaleai",
        "coinbase"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("abhay512/startup-hiring-ats-scraper").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = { "companies": [
        "stripe",
        "vercel",
        "anthropic",
        "figma",
        "linear",
        "retool",
        "scaleai",
        "coinbase",
    ] }

# Run the Actor and wait for it to finish
run = client.actor("abhay512/startup-hiring-ats-scraper").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "companies": [
    "stripe",
    "vercel",
    "anthropic",
    "figma",
    "linear",
    "retool",
    "scaleai",
    "coinbase"
  ]
}' |
apify call abhay512/startup-hiring-ats-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,abhay512/startup-hiring-ats-scraper"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/70YCuZT64AsbAl71t/builds/yyuPtCsjCLn3s0dvB/openapi.json