# Karriere.at Search Scraper (`jobsapi/karriere-at-jobs-search-scraper`) Actor

Scrape job listings from Karriere.at, Austria's leading job board. Extract job titles, companies, locations, salary ranges, contract types, and descriptions for Austrian recruitment and job market analysis.

- **URL**: https://apify.com/jobsapi/karriere-at-jobs-search-scraper.md
- **Developed by:** [Jobs API](https://apify.com/jobsapi) (community)
- **Categories:** Jobs, Automation, Developer tools
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $2.99 / 1,000 job details

This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.

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

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
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.
Actors are written with capital "A".

## 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.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## Karriere.at jobs search scraper

This Apify Actor extracts complete, source-backed job records locally or in Apify Cloud from the public [Karriere.at](https://www.karriere.at) search and detail pages.

### Modes

- `search` discovers jobs for one query and location, then enriches each result from its official detail page.
- `searchMultiple` runs bounded searches for each value in `queries` and deduplicates the detail records.
- `single` enriches one official `https://www.karriere.at/jobs/<numeric-id>` URL.
- `multiple` enriches a bounded list of official detail URLs.
- `startUrls` accepts official search or detail URLs.

The default input is in [`INPUT.json`](./INPUT.json). Reproducible examples are provided in `INPUT-single.json`, `INPUT-multiple.json`, `INPUT-search-multiple.json`, `INPUT-start-urls.json`, and `INPUT-negative.json`.

### Extraction contract

Each dataset row is written only after the detail page exposes a matching numeric ID, canonical URL, title, employer, location, and a sufficiently rich description. The mapper preserves published JSON-LD and HTML-derived descriptions, headings, bullets, sections, job facts, candidate criteria, employment, work model, location, salary, dates, company metadata, and explicit application links. Missing optional source values are omitted; the canonical job URL is never used as a fabricated application URL.

Rows are buffered until validation succeeds, deduplicated by official job ID and URL, and written with strict schemas. `RUN_SUMMARY`, `RUN_DIAGNOSTICS`, `RUN_SKIPS`, `REQUEST_RECEIPTS`, `RUN_HEALTH`, and `RUN_METADATA` stay in the key-value store rather than being emitted as job rows.

### Local verification

```text
npm install
npm test
npm run lint
npm run check
npm run validate
npx --yes apify-cli validate-schema
npx --yes apify-cli run --purge --input-file INPUT.json
```

The Actor uses ordinary native HTTPS requests with a normal browser-compatible `User-Agent`, bounded concurrency/timeouts, and a 5 MB response cap. It does not use a proxy, fingerprint spoofing, CAPTCHA/WAF bypass, or reader mirror. If the official site blocks access, the Actor finishes with structured KVS diagnostics and zero job rows.

# Actor input Schema

## `mode` (type: `string`):

search discovers jobs; searchMultiple runs several queries; single and multiple enrich exact detail URLs; startUrls accepts official search or detail URLs.

## `query` (type: `string`):

German job title, keyword, or sector.

## `queries` (type: `array`):

Queries for searchMultiple mode.

## `location` (type: `string`):

Optional Austrian city or region.

## `url` (type: `string`):

One official Karriere.at /jobs/<numeric-id> URL for single mode.

## `urls` (type: `array`):

Official Karriere.at detail URLs for multiple mode.

## `startUrls` (type: `array`):

Official Karriere.at search or detail URLs for startUrls mode.

## `maxItems` (type: `integer`):

Maximum complete records to write.

## `maxPages` (type: `integer`):

Bounded number of official search pages per query.

## `concurrency` (type: `integer`):

Maximum concurrent detail requests.

## `requestTimeoutSecs` (type: `integer`):

Timeout per official request in seconds.

## Actor input object example

```json
{
  "mode": "search",
  "query": "entwickler",
  "location": "Wien",
  "maxItems": 3,
  "maxPages": 2,
  "concurrency": 4,
  "requestTimeoutSecs": 25
}
```

# Actor output Schema

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

Complete source-backed public job records.

## `runState` (type: `string`):

Summary, diagnostics, skips, request receipts, health, and runtime metadata.

# 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 = {
    "mode": "search",
    "query": "entwickler",
    "location": "Wien",
    "maxItems": 3,
    "maxPages": 2,
    "concurrency": 4,
    "requestTimeoutSecs": 25
};

// Run the Actor and wait for it to finish
const run = await client.actor("jobsapi/karriere-at-jobs-search-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 = {
    "mode": "search",
    "query": "entwickler",
    "location": "Wien",
    "maxItems": 3,
    "maxPages": 2,
    "concurrency": 4,
    "requestTimeoutSecs": 25,
}

# Run the Actor and wait for it to finish
run = client.actor("jobsapi/karriere-at-jobs-search-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 '{
  "mode": "search",
  "query": "entwickler",
  "location": "Wien",
  "maxItems": 3,
  "maxPages": 2,
  "concurrency": 4,
  "requestTimeoutSecs": 25
}' |
apify call jobsapi/karriere-at-jobs-search-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,jobsapi/karriere-at-jobs-search-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/96FggHTMWTM8Kum3q/builds/aplTUfbRnhTZLxcee/openapi.json