Lever Jobs Scraper & Hiring Signals

Export public Lever job postings from company slugs or global Lever board URLs into structured hiring data. Lever Jobs Scraper returns titles, application URLs, locations, departments, teams, descriptions and available salary ranges for recruiting research, job-board feeds and account research.

Only public global Lever boards are supported. Supply your own company list. There is no built-in company discovery or EU-board support.

Quick start

1. Add a company slug from its global Lever board, such as spotify from https://jobs.lever.co/spotify.
2. Start with a small maximum number of postings and leave filters empty.
3. Run the Actor, then export the dataset as JSON, CSV or Excel.

{
  "companySlugs": ["spotify"],
  "limit": 10,
  "includeDescriptionHtml": false
}

Prefer a video guide? This short Apify walkthrough shows you how to set up and run an Actor. It uses a different Actor, but the setup steps are the same.

Ready-to-run examples

Choose a public example to see its settings before starting a run:

• Internships
• Fintech Company Jobs

What you get

One public global-Lever job row with its company slug, posting identity, title and available location, categories, text sections and application links. Optional salary ranges and HTML can be included when supplied. Requirements and benefits are not separately extracted, and missing scalar or nested fields retain their null or empty behavior.

Who is it for?

• Recruitment researchers reviewing known companies' public postings.
• Job-board teams importing source-linked jobs and available description sections.
• Workforce analysts comparing employer, location and disclosed-pay context.
• Data developers retaining posting identities for their own repeat-export reports.

How you can use the data

• Review one known global board. Use the existing spotify slug with ten postings and optional HTML off. Keep companySlug, jobId, title, hostedUrl and available descriptionPlain together. Turning HTML off does not mean every plain-text section is absent.
• Narrow a location or commitment sample. Use the documented London main-location filter or Internship work-type label for a small board export. These controls match source categories/text rather than a full-text keyword search, date interval or verified workplace-type filter.
• Retain source compensation and section context. Keep salaryRange and salaryDescriptionPlain with the listing URL. Lists can still contain markup despite contentPlain naming, while requirementsPlain and benefitsPlain remain null rather than separately parsed sections.
• Compare your own company snapshots. Join company slug and job ID with collection time in your destination. The total cap spans supplied boards in order, so an earlier board can fill it. Records are not balanced by employer or sorted by recency, and remote flags are inferred output context rather than a dedicated remote-only input.

Input settings

Setting	API key	Purpose
Lever company slugs	companySlugs	Required nonempty list of company slugs or global board URLs.
Maximum job postings	limit	Combined saved-row limit across companies. Form default 20.
Departments	departments	Match department categories.
Locations	locations	Match part of the main location text.
Teams	teams	Match team categories.
Work types / commitments	workTypes	Match commitment categories, such as Internship.
Include HTML descriptions	includeDescriptionHtml	Add formatted description and additional-content fields.

Detailed matching rules and defaults are in the input-field help. For example, set locations to ["London"] to narrow by location. Leave filters empty to include all available postings up to your limit.

Example inputs

Use the Quick start input as a small first run. Adjust the fields described above for your own data.

Output data

Each saved row represents a posting. This abbreviated, illustrative shape is not an observed job listing:

{
  "companySlug": "example-company",
  "leverRegion": "global",
  "jobId": "example-posting-id",
  "title": "Example role",
  "location": null,
  "department": null,
  "workType": null,
  "isRemote": false,
  "createdAt": null,
  "descriptionPlain": null,
  "salaryRange": null,
  "requirementsPlain": null,
  "benefitsPlain": null
}

Fields	Contents
companySlug, leverRegion, jobId, title	Company and posting identity. Region is global.
hostedUrl, applyUrl	Public posting and application destinations when supplied.
location, allLocations, normalizedLocation, country	Available location information.
department, team, workType, commitment	Lever category values. workType and commitment carry the same value.
workplaceType, isRemote	Available workplace category and a remote indicator inferred from it or location text.
createdAt, createdAtTimestamp, ageDays	Available posting date, timestamp and age at collection.
openingPlain, descriptionPlain, additionalPlain	Available text sections.
lists	Section titles and content. contentPlain currently repeats the supplied content and may contain markup.
requirementsPlain, benefitsPlain	Reserved fields, currently always null. These sections are not separately extracted.
salaryRange, salaryDescriptionPlain	Disclosed compensation when provided. Missing values remain null.
descriptionHtml, additionalHtml	Optional fields included only when requested.
source, scrapedAt	Source URL and collection timestamp.

JSON preserves nested sections, arrays and salary objects. Missing optional text is usually null. allLocations and lists can be empty arrays.

Download your results

Open your run's dataset, choose Export and select JSON, CSV or Excel. JSON keeps nested fields together. CSV and Excel are useful when you want to review the records in a spreadsheet.

See Apify's download and export guide for the available formats and field options.

Pricing

Pay-per-event pricing charges start once per run and item for each saved job posting. There are no separate error or status dataset rows. A run with no saved postings can still incur the start event.

Use a small shared cap and company list initially. See the live Pricing tab for current rates.

Tips for best results

• Use a real global Lever company slug or board URL. A guessed company name or another careers platform is not a supported board.
• Start with one board and an explicit shared cap. The cap does not limit the size of the board's source response.
• Filter known source categories and main-location text. Remote text matching is not equivalent to a workplace-type filter.
• Keep nested source sections and salary objects in JSON when needed. Optional lists can be empty and contentPlain can retain markup.
• Inspect RUN-SUMMARY after empty or partial work. A valid empty board differs from failed company requests.

Limits and caveats

Only global jobs.lever.co boards are supported. EU boards, arbitrary careers pages, login-only data, applications and candidate records are outside scope. Slugs are lowercased, so case-sensitive boards may not resolve. There is no built-in company discovery or affiliation with Lever.

The saved-row cap is at most ten thousand across the run, not a response-size cap or per-company allocation. Supplied company order can leave later boards unreached. There is no keyword, workplace-type, date-window or per-company limit control and no recency or balancing sort.

A valid board with no openings, or filters with no matches, can finish empty. Other companies can retain useful rows after one request fails. If no jobs are saved and every supplied company request fails, the current run fails. Consult RUN-SUMMARY rather than interpreting an unavailable board as private or deleted.

Optional source values can be null or empty. Remote status is inferred from exposed category or location text, not verified eligibility. Requirements and benefits remain reserved null fields, section content can contain markup, and compensation is only what the employer discloses. Repeat-export joins and additional analysis are your own workflow.

Automation and integrations

Save your settings for next time

Once you have an input that works for you, save it as an Apify task. This keeps your settings together so you can use them again without filling in the form from scratch.

Run on a schedule

Need fresh results regularly? You can schedule the Actor or a saved task to run at a time that suits you.

Each scheduled run collects the data again. If you want to compare results or highlight changes, add that step in your own workflow.

Send results to your other tools

Use n8n, Make or Zapier to connect this scraper to the rest of your workflow. For example, you could pass its results to an AI assistant or add records to a spreadsheet. Follow the Apify integration guides for your chosen tool.

For a custom connection, an Apify webhook can notify your app when a run finishes or fails. Your app can then fetch the results or handle the failure.

API usage

Want to collect this data from your own app or automation? The examples below send input to the scraper and show how to collect its results.

The Node.js and Python examples wait for the run to finish before reading its results. The cURL example starts the run and returns its details. Wait for that run to finish, then use its defaultDatasetId to fetch the results.

For setup instructions, see Apify's JavaScript client guide, Python client guide and Actor runs API reference.

cURL

curl -X POST 'https://api.apify.com/v2/acts/fetch_cat~lever-jobs-scraper/runs' \
  -H "Authorization: Bearer $APIFY_TOKEN" \
  -H 'Content-Type: application/json' \
  --data @- <<'JSON'
{
  "companySlugs": [
    "spotify"
  ],
  "limit": 10,
  "includeDescriptionHtml": false
}
JSON

Node.js

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('fetch_cat/lever-jobs-scraper').call({
  "companySlugs": [
    "spotify"
  ],
  "limit": 10,
  "includeDescriptionHtml": false
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

Python

import os
from apify_client import ApifyClient

client = ApifyClient(os.environ['APIFY_TOKEN'])
run = client.actor('fetch_cat/lever-jobs-scraper').call(run_input={'companySlugs': ['spotify'], 'limit': 10, 'includeDescriptionHtml': False})
print(client.dataset(run['defaultDatasetId']).list_items().items)

MCP and AI agents

You can ask your AI assistant to collect data with Lever Jobs Scraper & Hiring Signals and help you work with the results. The scraper returns the data, and your assistant can then summarize it, compare records or prepare notes.

Connect your assistant through the Apify MCP server. MCP gives your assistant a way to find this scraper, run it and read the results. Follow the official setup and sign-in guide for your app.

Easier setup with an Apify plugin

If you use a supported coding assistant, the official Apify plugin can set up the connection for you. It connects your assistant to Apify and includes instructions for common tasks. Follow the guide for your particular app.

Use Apify AI in Console

Prefer to keep everything in Apify? Open Apify AI in Console and ask it to find Fetch Cat's Lever Jobs Scraper & Hiring Signals. You can describe the data you want and ask questions about the results.

Apify AI is currently in beta. It asks for confirmation before starting an Actor, and normal run charges apply.

Choose your assistant

• Claude and Claude Code (Anthropic): Apify setup guide.
• ChatGPT and Codex (OpenAI): Apify setup guides.
• Grok Bot (xAI): Apify plugin guide.
• Gemini CLI (Google): MCP server setup guide. Use the server URL below with the HTTP configuration supported by Gemini CLI.

Connect just this scraper

To keep your setup focused on this scraper, add this server configuration to a compatible MCP client:

{
  "mcpServers": {
    "apify": {
      "url": "https://mcp.apify.com?tools=fetch_cat/lever-jobs-scraper"
    }
  }
}

Sign in to Apify when your client asks. If your client uses a Bearer token instead, follow its setup guide and keep the token in its secure configuration. Configuration formats vary by app, so use the linked guide if your client needs a different format.

Use Apify's general server

Already connected to the general Apify MCP server at https://mcp.apify.com? You can use it to find this scraper without adding another server. Ask your assistant to use Lever Jobs Scraper & Hiring Signals by Fetch Cat, or give it the identifier fetch_cat/lever-jobs-scraper.

Your assistant can check the available settings and retrieve the results from the returned run. If the run is still working, it should follow that run rather than start it again. Both connection options use Apify's hosted service.

Example requests

• “Use Fetch Cat’s Lever Jobs Scraper to collect up to 5 postings from global company slug spotify with HTML descriptions off and filters empty. Show source posting links and available plain text, leaving optional salaries unknown.”
• “Collect up to 5 spotify Lever postings matching main-location text London, with HTML descriptions enabled. Keep source categories and application links without inferring remote eligibility.”
• “Retrieve up to 5 spotify postings matching work-type category Internship with HTML off. Preserve job IDs, source links and collection times for my own comparison, and check the summary if no matching openings are returned.”

Normal Apify charges apply. Check the live Pricing tab before asking your assistant to run a larger batch.

Pay with x402

If your AI agent has a funded wallet, it can pay for Apify usage through x402. This experimental option lets an agent use Apify without a conventional account.

Apify AGI provides a prepaid API token with a spending cap after payment. Your agent can use that token to run this scraper through the Apify API or an authenticated MCP connection.

Some MCP setups also support paying for each request directly. That is a different payment option, so check the official guide for its availability.

Follow the official guide for wallet setup, supported payment options and current terms. Apify handles the payments. Keep wallet keys and payment tokens in your agent's secure configuration.

Other ways for agents to pay

Apify also supports MPP for prepaid access through AGI and Skyfire for eligible Actors. If your agent already uses one of these, see the agentic payment guide to choose the right setup.

FAQ

How do I find a Lever company slug?

Use the first path segment of a global Lever board URL. For https://jobs.lever.co/spotify, supply spotify or the complete board URL. Do not use a company name guessed from another careers platform.

Can I export Lever jobs to CSV or use them through an API?

Yes. Download the dataset from Apify, use the API examples above, or connect through Apify MCP. JSON is preferable when you need nested salary and section data.

Does this require a Lever login?

No. Only publicly available postings are collected. Your Apify API token is used to call Apify, not to access a private Lever account.

Why are results empty or optional fields missing?

A company can have no openings or no matches for your filters. Inspect RUN-SUMMARY for request failures. Department, salary and other optional values depend on what the company publishes. Requirements and benefits are not extracted into separate fields.

Can I request recent jobs or only remote roles?

There is no recent-date or dedicated remote-only input. You can filter on main-location text such as Remote, but this is not equivalent to filtering workplaceType. Sort or filter exported dates and remote indicators in your own workflow.

What if my target uses another careers platform?

Use the corresponding scraper below instead of passing its URL as a Lever company slug.

Related Actors

• Greenhouse Jobs Scraper — Public Greenhouse job boards.
• Ashby Jobs Scraper — Ashby-hosted openings.
• Workday Jobs Scraper — Workday career sites.
• SmartRecruiters Jobs Scraper — SmartRecruiters postings.
• Built In Jobs Scraper — Hiring research on Built In.

Support and feedback

For custom additions or integrations, email hello@fetchcat.dev.

Found an error or have a feature request? Open an issue with the run URL, a non-sensitive input example and what you expected.

Need help sharing it? See Apify’s guide to sharing a run when reporting an issue. Sharing a run can give the developer access to its input, logs and results, so use a run that contains no sensitive data. Please leave out API tokens, passwords, cookies, private documents and personal data. Use a public sample URL or a redacted example instead.

Tried this scraper? We'd love to hear how it worked for you. Leave a review to help others choose the right tool and help us improve it. Your feedback means a lot to us.

Made with care for curious people, AI agents and the possibilities in data. ♥