# Lever Jobs Scraper (`schnellscrapers/lever-jobs-scraper`) Actor
Scrape every active job posting from any Lever.co board — titles, locations, teams, departments, workplace type, full descriptions, responsibilities, and salary ranges. Live from the official Lever API. Filter by title, location, workplace type, country, date, or remote at the source.
- **URL**: https://apify.com/schnellscrapers/lever-jobs-scraper.md
- **Developed by:** [Nate Schnell](https://apify.com/schnellscrapers) (community)
- **Categories:** Jobs, Lead generation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks
- **User rating**: No ratings yet
## Pricing
from $0.70 / 1,000 postings
This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.
Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event
## What's an Apify Actor?
Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases.
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.
In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md):
```bash
npm install apify-client
```
In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md):
```bash
pip install apify-client
```
In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md):
````bash
# MacOS / Linux
curl -fsSL https://apify.com/install-cli.sh | bash
# Windows
irm https://apify.com/install-cli.ps1 | iex
```bash
In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md).
If your project is in a different language, use 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
### What does Lever Jobs Scraper do?
**Lever Jobs Scraper** pulls every active job posting from any company's Lever.co careers board, live from the official Lever Postings API. Paste the board slug (e.g. `spotify`, `coupa`, `aircall`) or any Lever URL, get back a clean dataset of every posting — titles, locations, teams, departments, workplace type, full HTML and plain-text descriptions, structured responsibilities and requirements, and salary ranges where Lever exposes them. Built for recruiters tracking competitor hiring, lead-gen pipelines targeting hiring companies, job aggregators backfilling postings, and analysts mapping talent demand.
### What data can you extract from Lever?
Each emitted record has 24 fields. The most useful ones:
- **Identity** — `id` (Lever posting UUID), `board` (the slug), `companyName` (when mapped via `companyMap`), `hostedUrl`, `applyUrl`
- **Title** — `title`
- **Location** — `location` (primary), `allLocations[]` (every city Lever lists), `country` (2-letter code)
- **Workplace** — `workplaceType` (`remote` / `hybrid` / `onsite` / `unspecified`)
- **Team & department** — `team`, `department`, `commitment` (Full-time, Intern, Contract, …), `level`
- **Timing** — `createdAt` (ISO 8601, converted from Lever's epoch ms)
- **Description** — `description` (HTML, ready to render), `descriptionPlain` (text, HTML stripped)
- **Benefits / EEO / pay disclosures** — `additional` (HTML), `additionalPlain` (text)
- **Responsibilities & requirements** — `lists[]`, an array of structured sub-sections like _What you'll do_, _Requirements_, _Nice to have_. Each entry has the section header (`text`), the HTML content, and optional plain text.
- **Salary** — `salaryRange` (`min`, `max`, `currency`, `interval`) and `salaryDescription` when Lever exposes them — typically present on ~1 in 3 US/Canada postings.
Every field is preserved with the original Lever values, so records join back cleanly to Lever's UUIDs.
### How to use Lever Jobs Scraper
1. Create a free Apify account.
2. Open **Lever Jobs Scraper** and click **Try for free**.
3. Paste one or more board slugs or Lever URLs into **Lever boards**. The slug is the segment that follows `jobs.lever.co/` in a company's careers URL — e.g. `https://jobs.lever.co/spotify` → `spotify`.
4. (Optional) Add filters: `Title includes`, `Location excludes`, `Workplace type`, `Country includes`, `Only postings created after`, `Remote only`, etc. Filters run before billing.
5. (Optional) Map slug → company name via **Company name overrides** (e.g. `spotify=Spotify`) so the `companyName` column is populated. Lever's API doesn't return a company name.
6. Click **Save & Start**. Each board returns in 1–10 seconds regardless of size — one HTTP call per board.
7. Download results from the **Storage** tab in JSON, CSV, Excel, XML, or HTML.
### How much does it cost?
Lever Jobs Scraper is **pay-per-result**: you're billed one `posting` event per emitted record, regardless of how many boards you query. Postings filtered out by your input filters are not billed.
The per-posting price scales down as your Apify plan goes up:
| Your Apify plan | Per posting | Per 1,000 |
|---|---:|---:|
| Free | $0.00095 | **$0.95** |
| Starter | $0.00090 | $0.90 |
| Scale | $0.00080 – $0.00070 | $0.80 – $0.70 |
| Business / Enterprise | $0.00060 – $0.00050 | $0.60 – $0.50 |
The Apify Free plan includes **$5/month of platform credit** — enough for roughly 5,000 free postings before you'd need to top up. There's no minimum spend per run; pull 1 posting or 50,000.
Cost tip: switching `includeContent`, `includeAdditional`, and `includeLists` to `false` doesn't change the per-posting price, but it cuts dataset size by ~80% if you only need titles, locations, and links.
### Input
Required: `boards` (array of slugs or URLs). Every other field is optional.
```json
{
"boards": ["spotify", "coupa", "https://jobs.lever.co/aircall"],
"companyMap": ["spotify=Spotify", "coupa=Coupa", "aircall=Aircall"],
"includeContent": true,
"includeAdditional": true,
"includeLists": true,
"includeSalary": true,
"parseContent": false,
"titleFilter": ["engineer", "designer"],
"locationExcludeFilter": ["india"],
"workplaceTypeFilter": ["remote", "hybrid"],
"departmentFilter": ["engineering"],
"remoteOnly": false,
"createdAfter": "2026-04-01",
"maxItems": 200
}
````
See the **Input** tab for every field with help text. Common patterns:
- Pull *everything* from one company: `{ "boards": ["spotify"] }`
- Just titles and links (cheap fast pull): `{ "boards": ["coupa"], "includeContent": false, "includeAdditional": false, "includeLists": false }`
- Remote engineering jobs across several companies: `{ "boards": ["spotify","aircall","coupa"], "remoteOnly": true, "departmentFilter": ["engineering"] }`
- LLM-friendly text dataset: `{ "boards": ["spotify"], "parseContent": true }`
- US-only roles posted this month: `{ "boards": ["spotify"], "countryFilter": ["US"], "createdAfter": "2026-05-01" }`
### Output
One record per active posting. Sample (truncated):
```json
{
"id": "1ff4a4e3-897c-4eab-9ee2-aa7d1d07a9d6",
"board": "spotify",
"companyName": "Spotify",
"title": "Account Executive - Backstage",
"hostedUrl": "https://jobs.lever.co/spotify/1ff4a4e3-897c-4eab-9ee2-aa7d1d07a9d6",
"applyUrl": "https://jobs.lever.co/spotify/1ff4a4e3-897c-4eab-9ee2-aa7d1d07a9d6/apply",
"location": "Toronto",
"allLocations": ["Toronto"],
"country": "CA",
"workplaceType": "hybrid",
"team": "Platform",
"department": "Operations and Business Support",
"commitment": "Permanent",
"level": null,
"createdAt": "2026-03-12T17:10:21.350Z",
"description": "As an Account Executive for Spotify Backstage ...
",
"descriptionPlain": "As an Account Executive for Spotify Backstage ...",
"additional": "The Canada base range for this position is $103,628 – $148,040 CAD plus equity ...
",
"additionalPlain": "The Canada base range for this position is $103,628 – $148,040 CAD plus equity ...",
"lists": [
{
"text": "What You'll Do",
"content": "- Identify and pursue new business opportunities ...
",
"contentPlain": null
}
],
"salaryRange": null,
"salaryDescription": null,
"scrapedAt": "2026-05-22T12:45:18.054Z",
"source": "https://api.lever.co/v0/postings/spotify?mode=json"
}
```
Empty boards return zero records (Lever responds 200 with `[]`). Boards that don't exist or have moved off Lever log a warning and skip — your run isn't billed for them.
### Integrations
Lever Jobs Scraper works with the full Apify integration set: **Make**, **Zapier**, **n8n**, **Slack**, **Google Drive**, **GitHub**, **Airbyte**, scheduled runs, and the Apify API. Trigger runs from your ATS or CRM, push fresh postings into a Sheet or a database, or fan out webhook notifications when new postings appear. See [Apify integrations](https://docs.apify.com/platform/integrations).
### Related actors
- [Greenhouse Jobs Scraper](https://apify.com/schnellscrapers/greenhouse-jobs-scraper) — for companies hosted on Greenhouse instead of Lever (Airbnb, Stripe, Figma).
- [Ashby Jobs Scraper](https://apify.com/schnellscrapers/ashby-jobs-scraper) — for companies hosted on Ashby instead of Lever (Linear, Vanta, Ramp).
- [Indeed Jobs Scraper](https://apify.com/schnellscrapers/indeed-jobs-scraper) — for jobs hosted on Indeed (millions of postings across all employers, not just Lever-using companies).
- For multi-ATS aggregation across Workday + Lever + Ashby + Greenhouse and 50 other systems, the closest fit on the Store is `fantastic-jobs/career-site-job-listing-api` — it's a DB query against a pre-crawled index, not a live scrape.
### FAQ
#### How does Lever Jobs Scraper work?
It hits `https://api.lever.co/v0/postings/{slug}?mode=json` — Lever's official public Postings API, documented at [github.com/lever/postings-api](https://github.com/lever/postings-api) — and normalizes the response into the dataset schema. No login, no proxy, no headless browser. Pass `eu: true` to query `api.eu.lever.co` for EU-resident boards.
#### Can I use Lever Jobs Scraper as an API?
Yes. Trigger a run via the Apify REST API:
```
POST https://api.apify.com/v2/acts/schnellscrapers~lever-jobs-scraper/runs?token=
```
The Apify console also exposes a `run-sync-get-dataset-items` endpoint that returns records inline when the run finishes — handy for synchronous integrations.
#### Can I use it in Python or Node.js?
```python
from apify_client import ApifyClient
client = ApifyClient(token="")
run = client.actor("schnellscrapers/lever-jobs-scraper").call(run_input={
"boards": ["spotify", "coupa"],
"companyMap": ["spotify=Spotify", "coupa=Coupa"],
"titleFilter": ["engineer"],
})
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
print(item["title"], item["companyName"], item["location"])
```
```js
import { ApifyClient } from 'apify-client';
const client = new ApifyClient({ token: '' });
const run = await client.actor('schnellscrapers/lever-jobs-scraper').call({
boards: ['spotify', 'coupa'],
companyMap: ['spotify=Spotify', 'coupa=Coupa'],
titleFilter: ['engineer'],
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
```
#### Is it legal to scrape Lever?
Lever job boards are public-facing and the Postings API is documented for third-party use at [github.com/lever/postings-api](https://github.com/lever/postings-api) — companies use the same endpoint to embed their careers page. Lever Jobs Scraper hits only the official API and respects `robots.txt`. As with any scraping, the data you collect is what's already publicly available; storing or republishing it must comply with the hiring company's terms and any applicable privacy laws (GDPR, CCPA).
#### Why is my company's board returning a 404?
The slug is the path segment in the company's Lever careers URL — `jobs.lever.co/`. Some companies have moved off Lever or use a custom-domain alias that maps to a different slug. Open the company's careers page and check the URL the listings load from. If you see a 404 in the logs, the run for that board is skipped at no charge.
#### Why is `companyName` null?
Lever's API doesn't return a company name — only the slug. Pass a `companyMap` entry like `spotify=Spotify` to label the records yourself. The slug is always present in the `board` field if you want to map externally.
#### How fresh is the data?
Live — every run hits Lever's API directly. Compare to DB-aggregator actors (e.g. `fantastic-jobs/career-site-job-listing-api`), which have an indexing lag of up to 30 minutes per their docs.
#### Does it return salary ranges?
Yes, when Lever exposes them. Salary fields are most consistently populated on US, Canada, and California-headquartered postings due to pay-transparency laws. Set `includeSalary: false` to drop them from the output.
#### Does it support EU Lever boards?
Yes. Set `eu: true` to query `api.eu.lever.co` instead of the global host. The global host transparently serves most EU boards too, so this is rarely needed.
### Your feedback
Found a bug, missing a field, or want a new filter? Open an issue on the actor's Issues tab or email me. Every report gets read.
# Actor input Schema
## `boards` (type: `array`):
Companies to pull postings from. Paste the board slug (e.g. `spotify`, `coupa`) or any Lever URL — `https://jobs.lever.co/spotify`, `https://api.lever.co/v0/postings/spotify`. The slug is the segment that follows `jobs.lever.co/` in a company's careers URL.
## `companyMap` (type: `array`):
Optional. Map board slugs to human-readable company names so the `companyName` column is populated (Lever's API doesn't return it). One entry per line in `slug=Company Name` format (e.g. `spotify=Spotify`, `insomniacookies=Insomnia Cookies`).
## `eu` (type: `boolean`):
Query `api.eu.lever.co` instead of the global `api.lever.co`. The global host serves every board; flip this only if you specifically need the EU endpoint.
## `includeContent` (type: `boolean`):
Include the main posting body (`description` HTML + `descriptionPlain` text) in each record. Turn off to shrink results by ~80% when you only need titles, locations, and links.
## `includeAdditional` (type: `boolean`):
Include Lever's `additional` section — usually benefits, EEO statements, and pay transparency disclosures (HTML + plain text).
## `includeLists` (type: `boolean`):
Include Lever's `lists` array — the bulleted sub-sections like "What you'll do", "Requirements", "Nice to have". Each entry has the section header, the HTML content, and (when `parseContent` is on) plain text.
## `includeSalary` (type: `boolean`):
Include `salaryRange` (min/max/currency/interval) and `salaryDescription` when Lever exposes them. Approximately 1 in 3 postings carry salary data depending on the board.
## `parseContent` (type: `boolean`):
Re-run HTML stripping over `description`, `additional`, and each `lists[].content` to populate `descriptionPlain`, `additionalPlain`, and `lists[].contentPlain` from the same source. Useful when feeding records into LLMs or full-text search.
## `titleFilter` (type: `array`):
Case-insensitive substring match against the posting title. A record is kept if any term matches (e.g. `engineer`, `designer`). Leave empty to keep all titles.
## `titleExcludeFilter` (type: `array`):
Drop postings whose title contains any of these substrings (e.g. `intern`, `manager`).
## `locationFilter` (type: `array`):
Substring match against the primary location and the full `allLocations` array (e.g. `new york`, `berlin`, `remote`).
## `locationExcludeFilter` (type: `array`):
Drop postings whose location matches any term (e.g. `india` to exclude India-based postings).
## `teamFilter` (type: `array`):
Substring match against `categories.team` (e.g. `platform`, `growth`).
## `departmentFilter` (type: `array`):
Substring match against `categories.department` (e.g. `engineering`, `design`, `sales`).
## `commitmentFilter` (type: `array`):
Substring match against `categories.commitment` (e.g. `full-time`, `intern`, `contract`). Free-form text in Lever — partial matches work best.
## `workplaceTypeFilter` (type: `array`):
Exact match against `workplaceType`. Valid values: `remote`, `hybrid`, `onsite`, `unspecified`.
## `countryFilter` (type: `array`):
Two-letter country codes Lever reports (e.g. `US`, `GB`, `DE`). Case-insensitive exact match.
## `companyFilter` (type: `array`):
Substring match against the company name you assigned via `companyMap`. Useful when one run covers many boards.
## `descriptionContains` (type: `array`):
Substring match across the description, additional, and plain-text fields (e.g. `python`, `kubernetes`, `visa sponsorship`). Auto-enables `includeContent` if both content fetches are off.
## `remoteOnly` (type: `boolean`):
Keep only postings whose `workplaceType` is `remote` or whose location string contains `remote`. Hybrid is excluded.
## `createdAfter` (type: `string`):
ISO 8601 date or timestamp (e.g. `2026-05-01` or `2026-05-01T00:00:00Z`). Drops postings whose `createdAt` is older. Leave blank to keep every active posting.
## `maxItems` (type: `integer`):
Hard cap on total records emitted across all boards. Useful for cost-bounded test runs. Leave at 0 to emit every matching posting.
## `maxItemsPerBoard` (type: `integer`):
Per-board cap on emitted records. Leave at 0 to emit every matching posting from each board.
## `dryRun` (type: `boolean`):
Fetch and parse the boards but do not write to the dataset. Use to preview without spending credits.
## Actor input object example
```json
{
"boards": [
"spotify",
"coupa"
],
"companyMap": [],
"eu": false,
"includeContent": true,
"includeAdditional": true,
"includeLists": true,
"includeSalary": true,
"parseContent": false,
"titleFilter": [],
"titleExcludeFilter": [],
"locationFilter": [],
"locationExcludeFilter": [],
"teamFilter": [],
"departmentFilter": [],
"commitmentFilter": [],
"workplaceTypeFilter": [],
"countryFilter": [],
"companyFilter": [],
"descriptionContains": [],
"remoteOnly": false,
"maxItems": 0,
"maxItemsPerBoard": 0,
"dryRun": false
}
```
# Actor output Schema
## `postings` (type: `string`):
Default dataset of posting records. Key fields: title, companyName, location, workplaceType, department, hostedUrl, description, salaryRange, createdAt.
# 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 '' with your token
const client = new ApifyClient({
token: '',
});
// Prepare Actor input
const input = {
"boards": [
"spotify",
"coupa"
],
"companyMap": [],
"titleFilter": [],
"titleExcludeFilter": [],
"locationFilter": [],
"locationExcludeFilter": [],
"teamFilter": [],
"departmentFilter": [],
"commitmentFilter": [],
"workplaceTypeFilter": [],
"countryFilter": [],
"companyFilter": [],
"descriptionContains": []
};
// Run the Actor and wait for it to finish
const run = await client.actor("schnellscrapers/lever-jobs-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 '' with your token.
client = ApifyClient("")
# Prepare the Actor input
run_input = {
"boards": [
"spotify",
"coupa",
],
"companyMap": [],
"titleFilter": [],
"titleExcludeFilter": [],
"locationFilter": [],
"locationExcludeFilter": [],
"teamFilter": [],
"departmentFilter": [],
"commitmentFilter": [],
"workplaceTypeFilter": [],
"countryFilter": [],
"companyFilter": [],
"descriptionContains": [],
}
# Run the Actor and wait for it to finish
run = client.actor("schnellscrapers/lever-jobs-scraper").call(run_input=run_input)
# Fetch and print Actor results from the run's dataset (if there are any)
print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
print(item)
# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start
```
## CLI example
```bash
echo '{
"boards": [
"spotify",
"coupa"
],
"companyMap": [],
"titleFilter": [],
"titleExcludeFilter": [],
"locationFilter": [],
"locationExcludeFilter": [],
"teamFilter": [],
"departmentFilter": [],
"commitmentFilter": [],
"workplaceTypeFilter": [],
"countryFilter": [],
"companyFilter": [],
"descriptionContains": []
}' |
apify call schnellscrapers/lever-jobs-scraper --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=schnellscrapers/lever-jobs-scraper",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "Lever Jobs Scraper",
"description": "Scrape every active job posting from any Lever.co board — titles, locations, teams, departments, workplace type, full descriptions, responsibilities, and salary ranges. Live from the official Lever API. Filter by title, location, workplace type, country, date, or remote at the source.",
"version": "0.1",
"x-build-id": "iZcGruCDvKyPMUMSc"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/schnellscrapers~lever-jobs-scraper/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-schnellscrapers-lever-jobs-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/schnellscrapers~lever-jobs-scraper/runs": {
"post": {
"operationId": "runs-sync-schnellscrapers-lever-jobs-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/schnellscrapers~lever-jobs-scraper/run-sync": {
"post": {
"operationId": "run-sync-schnellscrapers-lever-jobs-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
}
},
"components": {
"schemas": {
"inputSchema": {
"type": "object",
"required": [
"boards"
],
"properties": {
"boards": {
"title": "Lever boards",
"type": "array",
"description": "Companies to pull postings from. Paste the board slug (e.g. `spotify`, `coupa`) or any Lever URL — `https://jobs.lever.co/spotify`, `https://api.lever.co/v0/postings/spotify`. The slug is the segment that follows `jobs.lever.co/` in a company's careers URL.",
"items": {
"type": "string"
}
},
"companyMap": {
"title": "Company name overrides",
"type": "array",
"description": "Optional. Map board slugs to human-readable company names so the `companyName` column is populated (Lever's API doesn't return it). One entry per line in `slug=Company Name` format (e.g. `spotify=Spotify`, `insomniacookies=Insomnia Cookies`).",
"items": {
"type": "string"
}
},
"eu": {
"title": "Use EU API region",
"type": "boolean",
"description": "Query `api.eu.lever.co` instead of the global `api.lever.co`. The global host serves every board; flip this only if you specifically need the EU endpoint.",
"default": false
},
"includeContent": {
"title": "Include job description",
"type": "boolean",
"description": "Include the main posting body (`description` HTML + `descriptionPlain` text) in each record. Turn off to shrink results by ~80% when you only need titles, locations, and links.",
"default": true
},
"includeAdditional": {
"title": "Include benefits / extras",
"type": "boolean",
"description": "Include Lever's `additional` section — usually benefits, EEO statements, and pay transparency disclosures (HTML + plain text).",
"default": true
},
"includeLists": {
"title": "Include responsibilities & requirements",
"type": "boolean",
"description": "Include Lever's `lists` array — the bulleted sub-sections like \"What you'll do\", \"Requirements\", \"Nice to have\". Each entry has the section header, the HTML content, and (when `parseContent` is on) plain text.",
"default": true
},
"includeSalary": {
"title": "Include salary fields",
"type": "boolean",
"description": "Include `salaryRange` (min/max/currency/interval) and `salaryDescription` when Lever exposes them. Approximately 1 in 3 postings carry salary data depending on the board.",
"default": true
},
"parseContent": {
"title": "Re-derive plain text from HTML",
"type": "boolean",
"description": "Re-run HTML stripping over `description`, `additional`, and each `lists[].content` to populate `descriptionPlain`, `additionalPlain`, and `lists[].contentPlain` from the same source. Useful when feeding records into LLMs or full-text search.",
"default": false
},
"titleFilter": {
"title": "Title includes",
"type": "array",
"description": "Case-insensitive substring match against the posting title. A record is kept if any term matches (e.g. `engineer`, `designer`). Leave empty to keep all titles.",
"items": {
"type": "string"
}
},
"titleExcludeFilter": {
"title": "Title excludes",
"type": "array",
"description": "Drop postings whose title contains any of these substrings (e.g. `intern`, `manager`).",
"items": {
"type": "string"
}
},
"locationFilter": {
"title": "Location includes",
"type": "array",
"description": "Substring match against the primary location and the full `allLocations` array (e.g. `new york`, `berlin`, `remote`).",
"items": {
"type": "string"
}
},
"locationExcludeFilter": {
"title": "Location excludes",
"type": "array",
"description": "Drop postings whose location matches any term (e.g. `india` to exclude India-based postings).",
"items": {
"type": "string"
}
},
"teamFilter": {
"title": "Team includes",
"type": "array",
"description": "Substring match against `categories.team` (e.g. `platform`, `growth`).",
"items": {
"type": "string"
}
},
"departmentFilter": {
"title": "Department includes",
"type": "array",
"description": "Substring match against `categories.department` (e.g. `engineering`, `design`, `sales`).",
"items": {
"type": "string"
}
},
"commitmentFilter": {
"title": "Commitment includes",
"type": "array",
"description": "Substring match against `categories.commitment` (e.g. `full-time`, `intern`, `contract`). Free-form text in Lever — partial matches work best.",
"items": {
"type": "string"
}
},
"workplaceTypeFilter": {
"title": "Workplace type",
"type": "array",
"description": "Exact match against `workplaceType`. Valid values: `remote`, `hybrid`, `onsite`, `unspecified`.",
"items": {
"type": "string"
}
},
"countryFilter": {
"title": "Country includes",
"type": "array",
"description": "Two-letter country codes Lever reports (e.g. `US`, `GB`, `DE`). Case-insensitive exact match.",
"items": {
"type": "string"
}
},
"companyFilter": {
"title": "Company includes",
"type": "array",
"description": "Substring match against the company name you assigned via `companyMap`. Useful when one run covers many boards.",
"items": {
"type": "string"
}
},
"descriptionContains": {
"title": "Description contains",
"type": "array",
"description": "Substring match across the description, additional, and plain-text fields (e.g. `python`, `kubernetes`, `visa sponsorship`). Auto-enables `includeContent` if both content fetches are off.",
"items": {
"type": "string"
}
},
"remoteOnly": {
"title": "Remote only",
"type": "boolean",
"description": "Keep only postings whose `workplaceType` is `remote` or whose location string contains `remote`. Hybrid is excluded.",
"default": false
},
"createdAfter": {
"title": "Only postings created after",
"type": "string",
"description": "ISO 8601 date or timestamp (e.g. `2026-05-01` or `2026-05-01T00:00:00Z`). Drops postings whose `createdAt` is older. Leave blank to keep every active posting."
},
"maxItems": {
"title": "Maximum records (total)",
"minimum": 0,
"maximum": 1000000,
"type": "integer",
"description": "Hard cap on total records emitted across all boards. Useful for cost-bounded test runs. Leave at 0 to emit every matching posting.",
"default": 0
},
"maxItemsPerBoard": {
"title": "Maximum records per board",
"minimum": 0,
"maximum": 1000000,
"type": "integer",
"description": "Per-board cap on emitted records. Leave at 0 to emit every matching posting from each board.",
"default": 0
},
"dryRun": {
"title": "Dry run",
"type": "boolean",
"description": "Fetch and parse the boards but do not write to the dataset. Use to preview without spending credits.",
"default": false
}
}
},
"runsResponseSchema": {
"type": "object",
"properties": {
"data": {
"type": "object",
"properties": {
"id": {
"type": "string"
},
"actId": {
"type": "string"
},
"userId": {
"type": "string"
},
"startedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"finishedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"status": {
"type": "string",
"example": "READY"
},
"meta": {
"type": "object",
"properties": {
"origin": {
"type": "string",
"example": "API"
},
"userAgent": {
"type": "string"
}
}
},
"stats": {
"type": "object",
"properties": {
"inputBodyLen": {
"type": "integer",
"example": 2000
},
"rebootCount": {
"type": "integer",
"example": 0
},
"restartCount": {
"type": "integer",
"example": 0
},
"resurrectCount": {
"type": "integer",
"example": 0
},
"computeUnits": {
"type": "integer",
"example": 0
}
}
},
"options": {
"type": "object",
"properties": {
"build": {
"type": "string",
"example": "latest"
},
"timeoutSecs": {
"type": "integer",
"example": 300
},
"memoryMbytes": {
"type": "integer",
"example": 1024
},
"diskMbytes": {
"type": "integer",
"example": 2048
}
}
},
"buildId": {
"type": "string"
},
"defaultKeyValueStoreId": {
"type": "string"
},
"defaultDatasetId": {
"type": "string"
},
"defaultRequestQueueId": {
"type": "string"
},
"buildNumber": {
"type": "string",
"example": "1.0.0"
},
"containerUrl": {
"type": "string"
},
"usage": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "integer",
"example": 1
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
},
"usageTotalUsd": {
"type": "number",
"example": 0.00005
},
"usageUsd": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "number",
"example": 0.00005
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
}
}
}
}
}
}
}
}
```