# Greenhouse & Lever ATS Jobs Scraper (FreshActors) (`freshactors/greenhouse-lever-jobs-scraper`) Actor Reliable, always-fresh job postings normalized across Greenhouse and Lever ATS boards. Public JSON, no login. Monitored daily. By FreshActors. - **URL**: https://apify.com/freshactors/greenhouse-lever-jobs-scraper.md - **Developed by:** [Martin Čech](https://apify.com/freshactors) (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 $20.00 / 1,000 company jobs fetcheds 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/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 ## Greenhouse & Lever ATS Jobs Scraper — One Normalized Schema, No API Key Scrape **Greenhouse and Lever ATS job postings** from any company's public board into a single, stable JSON schema — no account, no login, no two-parser headache. ![Greenhouse & Lever Jobs Scraper — two ATS, one normalized schema](https://raw.githubusercontent.com/Freshactors/freshactors-assets/main/ats-screenshot.png) > ✅ **Last verified working: 2026-06-01.** Monitored by an automated daily canary. When an ATS changes its public API, we patch fast and log it in the changelog below. --- ### Why this Greenhouse & Lever ATS jobs scraper If you've ever tried to scrape Greenhouse and Lever jobs yourself, you know the catch: the two ATS platforms return **completely different JSON**, so you end up writing and maintaining two separate parsers — and re-fixing them every time a board shape shifts. This actor exists to kill that maintenance tax. - **One schema for two ATS.** Greenhouse (`boards-api.greenhouse.io`) and Lever (`api.lever.co`) are mapped into a single, stable job record. Query 100 companies uniformly instead of branching on which ATS each one uses. That normalization *is* the product. - **No fragile site to break.** Job data lives behind each company's own public JSON board token — there's no global search page, no rotating HTML, no anti-bot wall to fight. We read the lowest-risk, most stable source there is: the boards the companies already serve publicly. - **Auto-detects the ATS.** Pass a bare token (`gitlab`) or a full board URL (`https://jobs.lever.co/spotify`). `auto` mode tries Greenhouse, then Lever, so you don't have to know which a company uses. - **Per-company isolation + retries.** A dead, renamed, or private board is skipped — it never crashes the whole run. Transient errors retry with backoff. - **Versioned, monitored schema.** Every record carries `_schemaVersion`, and a daily canary confirms both ATS endpoints still parse — so your hiring-signal pipeline never breaks silently. The "always-fresh" promise is operational, not marketing: a scheduled canary scrapes a known board every day, alerts on a parse change, and the fix ships the same day with a changelog entry. ### What data you get Every posting — Greenhouse or Lever — comes back as **one normalized job record**. Fields the source ATS doesn't provide return `null` rather than disappearing, so your downstream schema stays predictable. | Field | Type | Description | |---|---|---| | `_type` | string | Always `job`. | | `_schemaVersion` | string | Output schema version (e.g. `1.0`). | | `_source` | string | `greenhouse` or `lever` — which ATS this record came from. | | `company` | string | Board token / company slug. | | `jobId` | string | ATS-native posting ID. | | `title` | string | Job title. | | `department` | string \| null | Department. | | `team` | string \| null | Team (Lever-rich). | | `location` | string \| null | Primary location. | | `allLocations` | string[] | All listed locations. | | `workplaceType` | string \| null | `remote` / `hybrid` / `onsite` where provided. | | `commitment` | string \| null | e.g. `Permanent`, `Contract`. | | `country` | string \| null | Country code where provided. | | `url` | string | Public posting URL. | | `applyUrl` | string \| null | Direct apply URL. | | `postedAt` | string \| null | ISO timestamp posted. | | `updatedAt` | string \| null | ISO timestamp updated. | | `descriptionText` | string \| null | Full description text (when `includeDescription` is on). | | `_scrapedAt` | string | ISO timestamp this record was fetched. | **Modes:** the `ats` input controls how bare tokens are resolved — `auto` (try Greenhouse, then Lever), `greenhouse`, or `lever`. Full board **URLs are auto-detected regardless of this setting.** ### Use cases - **Sales intelligence / hiring-signal tracking.** Watch which companies are hiring AI engineers, opening a new office, or staffing a GTM team. Searching for a *Greenhouse and Lever jobs API* to feed your lead-scoring model? This is the structured feed — `department`, `team`, `location`, `postedAt` per posting. - **Recruiting & talent sourcing.** Aggregate live openings across dozens of target employers into one table. Filter by `workplaceType: remote` or `commitment` without writing a Lever-vs-Greenhouse adapter. - **Job boards & aggregators.** Building a niche board and need to *scrape Greenhouse and Lever ATS jobs* into a uniform feed? Point the actor at your company list and ingest normalized records on a schedule. - **Labor-market & VC research.** Track headcount-growth signals across a portfolio. `postedAt` / `updatedAt` give you a clean time series of when roles open across companies — no manual board-watching. ### Input | Field | Type | Required | Notes | |---|---|---|---| | `companies` | string[] | ✅ | Board tokens (`gitlab`) or board URLs (`https://jobs.lever.co/spotify`, `https://boards.greenhouse.io/airbnb`). One per row. | | `ats` | string | — | `auto` (try Greenhouse then Lever) / `greenhouse` / `lever`. Default `auto`. URLs auto-detect regardless. | | `includeDescription` | boolean | — | Fetch full description text per posting. Default `true`. | | `maxJobsPerCompany` | integer | — | Cap per company (1–5000). Default `1000`. | **Auto-detect mode** (mixed tokens + URLs): ```json { "companies": ["gitlab", "https://jobs.lever.co/spotify", "airbnb"], "ats": "auto", "includeDescription": true, "maxJobsPerCompany": 1000 } ```` **Greenhouse-only mode** (bare tokens you know are Greenhouse): ```json { "companies": ["gitlab", "airbnb", "stripe"], "ats": "greenhouse", "includeDescription": false, "maxJobsPerCompany": 500 } ``` **Lever-only mode:** ```json { "companies": ["spotify", "netflix"], "ats": "lever", "includeDescription": true } ``` ### Output sample A real normalized Lever record: ```json { "_type": "job", "_schemaVersion": "1.0", "_source": "lever", "company": "spotify", "jobId": "1ff4a4e3-0000-0000-0000-000000000000", "title": "Account Executive - Backstage", "department": "Operations and Business Support", "team": "Platform", "location": "Toronto", "allLocations": ["Toronto"], "workplaceType": "hybrid", "commitment": "Permanent", "country": "CA", "url": "https://jobs.lever.co/spotify/1ff4a4e3-...", "applyUrl": "https://jobs.lever.co/spotify/1ff4a4e3-.../apply", "postedAt": "2026-03-12T17:10:21.350Z", "updatedAt": null, "descriptionText": "About the role...", "_scrapedAt": "2026-06-01T09:14:02.118Z" } ``` A Greenhouse record (note ATS-specific gaps come back `null`, not missing): ```json { "_type": "job", "_schemaVersion": "1.0", "_source": "greenhouse", "company": "gitlab", "jobId": "8503792002", "title": "AI Engineer", "department": "Enterprise Applications", "team": null, "location": "Remote, US", "allLocations": ["Remote, US"], "workplaceType": "remote", "commitment": null, "country": null, "url": "https://job-boards.greenhouse.io/gitlab/jobs/8503792002", "applyUrl": "https://boards.greenhouse.io/gitlab/jobs/8503792002#app", "postedAt": "2026-05-29T07:49:29-04:00", "updatedAt": "2026-05-29T07:49:29-04:00", "descriptionText": "GitLab is...", "_scrapedAt": "2026-06-01T09:14:02.090Z" } ``` ### Pricing Pay-per-event — **no subscription**. You pay only for the boards you fetch and the postings you receive: | Event | Price (USD) | When it fires | |---|---|---| | **Company jobs fetched** | **$0.02** | Once per company board successfully fetched. | | **Job posting fetched** | **$0.0005** | Once per job posting returned. | **Worked example — "how much do 100 results cost?"** Say you scrape **5 companies** and get **100 job postings** total: - Boards: 5 × $0.02 = **$0.10** - Postings: 100 × $0.0005 = **$0.05** - **Total: $0.15** for 100 normalized jobs across 5 companies. Scale it up: 50 companies × 1,000 postings each = 50 × $0.02 + 50,000 × $0.0005 = **$1.00 + $25.00 = $26.00** for 50,000 normalized postings. ### FAQ **Is scraping Greenhouse & Lever ATS jobs legal?** This actor reads **public, non-personal** job-posting data from companies' own public ATS boards — the same data their careers pages serve to any visitor. No login, no personal data. Use responsibly and in line with applicable terms and laws. **Do I need an API key?** No. There's no Greenhouse or Lever API key, no account, and no login. You provide a list of company board tokens or URLs and the actor reads their public JSON boards. **How do I find a company's board token?** It's the slug in their careers URL — `boards.greenhouse.io/**gitlab**` or `jobs.lever.co/**spotify**`. You can paste either the bare token or the full URL. **What's the difference between Greenhouse and Lever in the output?** None, by design — both are mapped to the same schema. The `_source` field tells you which ATS the record came from. Lever boards tend to populate `team`, `commitment`, and `country`; Greenhouse populates `department`. Missing fields return `null`. **How often is the data updated?** It's live — every run fetches the companies' current public boards in real time. The *actor itself* is monitored by a daily canary so parsing stays correct as ATS endpoints evolve. **Can I get the full job description text?** Yes. Set `includeDescription: true` (the default) and each posting includes `descriptionText`. Turn it off to fetch faster and lighter when you only need titles, locations, and metadata. **Can I scrape many companies at once?** Yes — pass as many tokens/URLs in `companies` as you need. Each board is fetched in isolation; a dead or private board is skipped rather than failing the run. Use `maxJobsPerCompany` (1–5000) to cap per-company volume. **Does it handle remote / hybrid filtering?** The output includes `workplaceType` (`remote` / `hybrid` / `onsite` where the ATS provides it), plus `location` and `allLocations[]`, so you can filter downstream. **What if a company uses neither Greenhouse nor Lever?** That board simply returns no jobs and is skipped — it won't crash the run. This actor covers Greenhouse and Lever specifically. **Can I get salary or applicant data?** No. Public ATS boards don't expose salary or applicant data, so the actor doesn't either — it returns only the public posting fields listed above. ### Other FreshActors tools | FreshActors actor | What it scrapes | |---|---| | [App Store Scraper](https://apify.com/freshactors/app-store-scraper) | Apple App Store — app details, search, reviews | | [Google Play Scraper](https://apify.com/freshactors/google-play-scraper) | Google Play — app details + reviews | | [Shopify App Store Scraper](https://apify.com/freshactors/shopify-app-store-scraper) | Shopify App Store — app details, reviews, discovery | | [Redfin Scraper](https://apify.com/freshactors/redfin-scraper) | Redfin — US real-estate listings | | [Greenhouse & Lever Jobs Scraper](https://apify.com/freshactors/greenhouse-lever-jobs-scraper) | Greenhouse + Lever — normalized job postings | ### Reliability Staying fresh is the whole point of FreshActors. A scheduled **daily canary** scrapes a known Greenhouse board and a known Lever board, validates the normalized schema, and alerts the moment a parse changes. When an ATS shifts its public JSON, we patch the same day and record it in the changelog below. Every record is stamped with `_schemaVersion` and `_scrapedAt` so you always know what shape you're consuming and when it was fetched. **Changelog** - **2026-06-01** — v1.0 launch. Normalized Greenhouse + Lever jobs, ATS auto-detection, full descriptions, per-company isolation, daily canary monitoring. **Legal note:** Reads public, non-personal job-posting data from companies' own public ATS boards (the same data their careers pages serve). No login, no personal data. Use responsibly and in line with applicable terms and laws. *Found a problem? Open an issue on the actor — issues are answered fast.* # Actor input Schema ## `companies` (type: `array`): Company board tokens (e.g. gitlab) or full board URLs (e.g. https://jobs.lever.co/spotify, https://boards.greenhouse.io/airbnb). One per row. ## `ats` (type: `string`): Which ATS bare tokens belong to. 'auto' tries Greenhouse, then Lever. (URLs are auto-detected regardless.) ## `includeDescription` (type: `boolean`): Fetch the full job description text for each posting. ## `maxJobsPerCompany` (type: `integer`): Cap on postings returned per company (1–5000). ## Actor input object example ```json { "companies": [ "gitlab", "https://jobs.lever.co/spotify" ], "ats": "auto", "includeDescription": true, "maxJobsPerCompany": 1000 } ``` # Actor output Schema ## `results` (type: `string`): Normalized job postings. # 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 = { "companies": [ "gitlab", "https://jobs.lever.co/spotify" ] }; // Run the Actor and wait for it to finish const run = await client.actor("freshactors/greenhouse-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 = { "companies": [ "gitlab", "https://jobs.lever.co/spotify", ] } # Run the Actor and wait for it to finish run = client.actor("freshactors/greenhouse-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 '{ "companies": [ "gitlab", "https://jobs.lever.co/spotify" ] }' | apify call freshactors/greenhouse-lever-jobs-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=freshactors/greenhouse-lever-jobs-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Greenhouse & Lever ATS Jobs Scraper (FreshActors)", "description": "Reliable, always-fresh job postings normalized across Greenhouse and Lever ATS boards. Public JSON, no login. Monitored daily. By FreshActors.", "version": "1.0", "x-build-id": "Ti3y3hevZTz1UDsmM" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/freshactors~greenhouse-lever-jobs-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-freshactors-greenhouse-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/freshactors~greenhouse-lever-jobs-scraper/runs": { "post": { "operationId": "runs-sync-freshactors-greenhouse-lever-jobs-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/freshactors~greenhouse-lever-jobs-scraper/run-sync": { "post": { "operationId": "run-sync-freshactors-greenhouse-lever-jobs-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "companies" ], "properties": { "companies": { "title": "Companies", "type": "array", "description": "Company board tokens (e.g. gitlab) or full board URLs (e.g. https://jobs.lever.co/spotify, https://boards.greenhouse.io/airbnb). One per row.", "items": { "type": "string" } }, "ats": { "title": "ATS hint", "enum": [ "auto", "greenhouse", "lever" ], "type": "string", "description": "Which ATS bare tokens belong to. 'auto' tries Greenhouse, then Lever. (URLs are auto-detected regardless.)", "default": "auto" }, "includeDescription": { "title": "Include full descriptions", "type": "boolean", "description": "Fetch the full job description text for each posting.", "default": true }, "maxJobsPerCompany": { "title": "Max jobs per company", "minimum": 1, "maximum": 5000, "type": "integer", "description": "Cap on postings returned per company (1–5000).", "default": 1000 } } }, "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 } } } } } } } } } } ```