# Greenhouse Jobs Scraper & API (`jobo.world/greenhouse-jobs-scraper-api`) Actor Scrape jobs directly from Greenhouse ATS via one fast API. Pull live roles from top tech companies like Airbnb, Stripe & Discord. Zero ghost jobs, verified daily — built for job boards, AI agents & tech hiring research. - **URL**: https://apify.com/jobo.world/greenhouse-jobs-scraper-api.md - **Developed by:** [Enrico](https://apify.com/jobo.world) (community) - **Categories:** Jobs - **Stats:** 229 total users, 63 monthly users, 97.2% runs succeeded, 3 bookmarks - **User rating**: 5.00 out of 5 stars ## Pricing $0.99 / 1,000 jobs 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 Jobs Scraper & API | Scrape Greenhouse ATS Jobs Search **job listings** directly from **Greenhouse ATS** — the leading recruitment platform used by **Airbnb, Stripe, Discord, Figma, Notion, Datadog, Plaid**, and thousands of high-growth tech companies. Query across **8,000+ indexed companies** in a single normalized response. Open the actor on Apify, hit **Try for free**, and run with the default input (`queries: ["Software Engineer", "Product Manager"]`). Use it to build job boards, power AI agents, run market research, or feed an HR tech product. [![Run on Apify](https://img.shields.io/badge/Run%20on-Apify-blue)](https://apify.com/jobo.world/greenhouse-jobs-scraper-api) [![Service Status](https://img.shields.io/badge/Service%20Status-jobo.world%2Fstatus-brightgreen)](https://jobo.world/status) --- ### What can Greenhouse Jobs Scraper do? - Query **8,000+ Greenhouse companies** — from unicorns like Airbnb and Stripe to hot startups — with one normalized schema - Filter by **work model, experience level, salary range, skills, and companies** - **De-duplicate** the same role before results return - Exclude noise with **negative-keyword syntax** (prefix any query token with `-`) - **Optionally** attach the full company profile — industries, funding, leadership, ratings, tech stack, H1B history - Run on Apify with **scheduling, monitoring, and webhooks**, and integrate with **Zapier, Make, Slack, or HTTP** - Download results as **JSON, CSV, or XLSX** --- ### Input Configure the actor on the **Input** tab in the Apify UI. Every field is optional; leaving them empty returns the broadest possible result set. #### Search The core of every run. `queries` accepts up to **5** titles or keywords (OR-ed together); adding more rarely helps — narrow with filters instead. | Parameter | Type | Description | |-----------|------|-------------| | `queries` | Array (≤5) | Job titles or keywords. Multiple values are OR-ed. Prefix any entry with `-` to exclude (`["Software Engineer", "-staff"]`). | | `locations` | Array | Cities, regions, or countries. Geocoded server-side for accurate matching. | #### Filters Faceted filters that narrow the result set. Salary filters work in USD; jobs without a disclosed salary are excluded when either is set. | Parameter | Type | Description | |-----------|------|-------------| | `work_models` | Array | `remote`, `hybrid`, `onsite`. | | `employment_types` | Array | `full-time`, `part-time`, `contract`, `internship`, `freelance`, `temporary`. | | `experience_levels` | Array | `intern`, `entry`, `mid`, `senior`, `lead`, `executive`. | | `skills_include` | Array | Only return jobs requiring ANY of these skills. Matched against AI-extracted qualifications. | | `skills_exclude` | Array | Exclude jobs requiring ANY of these skills. | | `companies_include` | Array | Only return jobs from these company names. | | `companies_exclude` | Array | Exclude jobs from these companies. | | `min_salary_usd` | Integer | Minimum annual USD salary. | | `max_salary_usd` | Integer | Maximum annual USD salary. | | `posted_after` | String | ISO 8601 (`2025-01-01T00:00:00Z`) or relative (`7 days ago`, `1 month`). | #### Company enrichment | Parameter | Type | Default | Description | |-----------|------|---------|-------------| | `include_company_details` | Boolean | `false` | **Off by default** — `company` carries a lightweight preview. Set `true` to replace it with the full enriched profile (companies are de-duplicated, fetched once per run; slower, more API calls). | #### Pagination | Parameter | Type | Default | Description | |-----------|------|---------|-------------| | `page` | Integer | `1` | Page number (max **20**). To go deeper, refine your filters instead of paging. | | `page_size` | Integer | `50` | Results per page (max **100**). | --- ### Output Each dataset row uses Jobo Connect's normalized job shape; the `source` field is always `"greenhouse"` for this actor. The full JSON Schema is on the **Dataset Schema** tab in the Apify UI. The **Output** tab offers two views: *Greenhouse Job Listings* (jobs with a lightweight company preview) and *Company details* (the full company profile, populated when `include_company_details` is enabled). #### Job fields | Name | Description | Type | |------|-------------|------| | `id` | Stable Jobo job identifier | uuid | | `title` | Raw job title | text | | `normalized_title` | Canonical title for grouping | text | | `description` | Full job description, HTML stripped | text | | `summary` | 2–3 sentence AI role recap | text | | `listing_url` | Canonical listing URL on Greenhouse | uri | | `apply_url` | Direct apply URL | uri | | `locations` | Array of `{location, city, region, country, latitude, longitude}` (geocoded when possible) | object[] | | `compensation` | `{min, max, currency, period}` | object | | `employment_type` | `full_time` / `part_time` / `contract` / `internship` / `freelance` / `temporary` | text | | `workplace_type` | `remote` / `hybrid` / `onsite` | text | | `experience_level` | `entry` / `mid` / `senior` / `lead` / `executive` | text | | `qualifications` | `must_have` / `preferred`, each with typed `skills` (`{name, type: hard\|soft}`), `education`, `certifications` | object | | `responsibilities` | Bullet list extracted from the description | text[] | | `benefits` | Bullet list extracted from the description | text[] | | `is_work_auth_required` | Work authorization required | bool | | `is_h1b_sponsor` | Employer sponsors H1B | bool | | `is_clearance_required` | Security clearance required | bool | | `source` | Always `"greenhouse"` for this actor | text | | `date_posted` | When the role was posted | timestamp | | `valid_through` | Expiry timestamp (null in most cases) | timestamp | | `created_at` | When Jobo first indexed the job | timestamp | | `updated_at` | Last time Jobo refreshed the job | timestamp | #### Company fields `company` is always present. By default it carries only the **preview** fields below; set `include_company_details: true` to replace it with the full enriched profile. **Preview (always present)** | Name | Description | Type | |------|-------------|------| | `id` | Stable Jobo company identifier — use as your primary key | uuid | | `name` | Trade name | text | | `website` | Company marketing website | text | | `logo_url` | Hosted logo URL | text | | `summary` | Short company blurb | text | | `industries` | Vertical industry labels | text[] | | `details_url` | Link to `GET /api/companies/{id}` for the full profile | uri | **Enriched (when `include_company_details` is on)** | Name | Description | Type | |------|-------------|------| | `legal_name` | Registered legal entity name | text | | `primary_industry` | Main industry label | text | | `company_size` | Headcount band, e.g. `1001-5000` | text | | `revenue` | Annual revenue band | text | | `founding_year` | Year founded | text | | `headquarters_location` | HQ city / region | text | | `country_code` | HQ country code | text | | `operating_status` | `active` / `closed` | text | | `ipo_status` | `private` / `ipo` / `delisted` | text | | `company_type` | `for_profit` / `non_profit` | text | | `stock_symbol` | Ticker symbol | text | | `stock_exchange` | Listing exchange | text | | `funding_stage` | Latest funding stage | text | | `total_funding` | Total funding raised | text | | `investors` | Investor names | text[] | | `funding_rounds` | Per-round detail (`investment_type`, `announced_on`, `raised_amount`, …) | object[] | | `founders` | Founder names | text[] | | `leadership` | `{name, title, linkedin_url, avatar_url}` | object[] | | `ratings` | `{source, rating, url, review_count}` (Glassdoor, etc.) | object[] | | `press_references` | `{url, posted_on, title, publisher}` | object[] | | `h1b_annual_job_counts` | `{year, count}` H1B history | object[] | | `technology_list` | Detected technologies | text[] | | `tech_stack` | `{name, categories}` | object[] | | `page_rank` | Domain authority score | number | | `leadership_display` | Display tag — `"Name — Title"` | text[] | | `ratings_display` | Display tag — `"Glassdoor 4.3 (2.1k)"` | text[] | | `funding_display` | Display tag — `"Series F · $15.4B"` | text[] | The complete company schema (every field) is on the **Dataset Schema** tab and at [docs.jobo.world/api-reference/companies/schema](https://docs.jobo.world/api-reference/companies/schema). Use `company.details_url` with your `X-Api-Key` to re-fetch a profile on demand. --- ### Quick-start input examples **Remote engineering roles** ```json { "queries": ["Software Engineer"], "work_models": ["remote"], "page_size": 50 } ```` **Senior+ roles in San Francisco, $180k+** ```json { "queries": ["Software Engineer"], "locations": ["San Francisco"], "experience_levels": ["senior", "lead"], "min_salary_usd": 180000, "page_size": 50 } ``` **Skills-filtered, US-only, $90k+** ```json { "queries": ["Backend Engineer"], "skills_include": ["Go", "Kubernetes", "PostgreSQL"], "skills_exclude": ["PHP"], "locations": ["United States"], "min_salary_usd": 90000, "page_size": 100 } ``` **Negative-keyword filter** ```json { "queries": ["Software Engineer", "-staff", "-principal"], "experience_levels": ["mid", "senior"], "page_size": 50 } ``` *** ### Tips & advanced options - **Pagination cap.** `page_size` maxes at 100 and `page` at 20. For bulk downloads (>2k rows) use **[ATS Jobs Feed](https://apify.com/jobo.world/ats-jobs-feed)** instead — it uses cursor pagination and pulls up to 1,000 rows per batch. - **`source` field is always `"greenhouse"`.** Every row carries this fixed value — useful for confirming origin when mixing datasets from multiple actors. - **`industries` empty for some companies.** Industries come from Jobo's enrichment pipeline; long-tail SMBs may show `industries: []`. - **Geocoding is best-effort.** Loose strings like `"Remote"` or `"Worldwide"` won't geocode; the raw `location` string is always preserved. - **Salary normalization.** All salary filters work in USD; source currencies (EUR, GBP, INR, etc.) are converted server-side using current FX. *** ### Use cases | Industry | Use case | |----------|----------| | **Job Boards** | Build Greenhouse-focused aggregators with normalized, richly structured data | | **AI Agents** | Power career chatbots and résumé-matching agents against Greenhouse's tech-company inventory | | **HR Tech** | Build market-intel dashboards scoped to the companies that use Greenhouse | | **Recruiting** | Source candidates and roles at Airbnb, Stripe, Discord, Figma, and 8,000+ peers | | **Salary Research** | Benchmark compensation across Greenhouse's high-growth customer base | | **Market Research** | Track sector hiring velocity through one of the most data-rich ATS ecosystems | *** ### Is it legal to scrape ATS job listings? Our scrapers are ethical and do not extract any private user data, such as email addresses, gender, or location. They only extract what the user has chosen to share publicly. We therefore believe that our scrapers, when used for ethical purposes by Apify users, are safe. However, you should be aware that your results could contain personal data. Personal data is protected by the GDPR in the European Union and by other regulations around the world. You should not scrape personal data unless you have a legitimate reason to do so. If you're unsure whether your reason is legitimate, consult your lawyers. *** ### FAQ #### Should I use this actor or the multi-ATS ATS Jobs Search? Use **this actor** when you only care about Greenhouse — simpler input, identical output schema. Use **[ATS Jobs Search](https://apify.com/jobo.world/ats-jobs-search)** when you want to query Greenhouse alongside Lever, Ashby, Workday, and 53 other ATSes in one call. #### Should I use this actor or ATS Jobs Feed? Use **Greenhouse Jobs Scraper** for filtered, paginated queries (job-board UIs, AI agents, real-time lookups). Use **[ATS Jobs Feed](https://apify.com/jobo.world/ats-jobs-feed)** for bulk download (data pipelines, full-inventory sync) — cursor pagination, 1,000 jobs per batch, built for high throughput. #### Are duplicates de-duped? Yes — Jobo Connect de-duplicates by (company + canonical title + listing URL) before returning results. #### Can I filter by salary? Yes — `min_salary_usd` and `max_salary_usd`, normalized to USD server-side. Jobs without a disclosed salary are excluded when either filter is set. #### How often is data updated? Jobs are verified **daily**. Expired listings are removed within 24 hours. #### Where can I check if the Jobo API is up? At **[jobo.world/status](https://jobo.world/status)** — the live status page for the Jobo Connect API behind this actor. *** ### Related actors | Actor | Best for | |-------|----------| | **[ATS Jobs Search](https://apify.com/jobo.world/ats-jobs-search)** | All 57 ATSes in one call | | **[ATS Jobs Feed](https://apify.com/jobo.world/ats-jobs-feed)** | Bulk download for data pipelines (cursor pagination, 1k/batch) | | **[Lever Jobs Scraper](https://apify.com/jobo.world/lever-jobs-scraper-api)** | VC-backed startups | | **[Workday Jobs Scraper](https://apify.com/jobo.world/workday-jobs-scraper-api)** | Fortune 500 enterprises | | **[Crunchbase Company Lookup](https://apify.com/jobo.world/crunchbase-company-lookup)** | Pair with `company.details_url` for funding / leadership data | *** ### Changelog #### 2.2 - **Job description in the listing view.** The full `description` field now appears directly in the Job Listings view. - **Company enrichment is opt-in.** `include_company_details` now defaults to off — the listing view carries a lightweight company preview, and the **Company details** view holds the full profile when enabled. #### 2.1 - **Company enrichment (opt-in).** `include_company_details` replaces the lightweight company preview with the full company profile — funding, leadership, ratings, tech stack, H1B sponsorship, acquisitions, investors, and more — fetched once per unique company. Off by default — enable it when you need company data. - **New "Company details" output view**. #### 2.0 - Richer per-job shape: AI-extracted `qualifications` (typed hard/soft skills, education, certifications), `responsibilities[]`, `benefits[]`, `summary`, and `normalized_title`. - Geocoded `locations[]` (resolved city / region / country / lat / lon). - New filters: salary range (`min_salary_usd` / `max_salary_usd`), skills include/exclude, companies include/exclude, work model, experience level, employment type, and negative query syntax. - Work-authorization signals: `is_work_auth_required`, `is_h1b_sponsor`, `is_clearance_required`. - Existing inputs (`queries`, `locations`, `posted_after`, `page`, `page_size`) are unchanged from v1.x. *** ### About Jobo Jobo provides comprehensive job data infrastructure for developers and businesses. Our ATS Jobs Database powers job boards, AI agents, and HR tech platforms worldwide. - **Website**: [jobo.world](https://jobo.world) - **Enterprise API**: [jobo.world/enterprise](https://jobo.world/enterprise) - **API status**: [jobo.world/status](https://jobo.world/status) - **Support**: enrico@jobo.world # Actor input Schema ## `queries` (type: `array`): Job titles or keywords (e.g., 'Software Engineer', 'Backend Developer'). Multiple values are OR-ed. Up to 5 keywords. Adding more rarely improves results — narrow your filters (skills, companies, locations) for better matches. ## `locations` (type: `array`): Cities, regions, or countries (e.g., 'San Francisco', 'United Kingdom'). Geocoded server-side for better matching. ## `work_models` (type: `array`): Where the work is performed. Leave empty for all. ## `employment_types` (type: `array`): Filter by employment type. Leave empty for all. ## `experience_levels` (type: `array`): Filter by seniority. Leave empty for all. ## `skills_include` (type: `array`): Only return jobs that require ANY of these skills (e.g., 'Python', 'React', 'AWS'). Matched case-insensitively against the AI-extracted qualifications. ## `skills_exclude` (type: `array`): Exclude jobs that require ANY of these skills. ## `companies_include` (type: `array`): Only return jobs from these specific Greenhouse companies (e.g., 'Stripe', 'Anthropic'). Matched case-insensitively by company name. ## `companies_exclude` (type: `array`): Exclude jobs from these companies. Useful for filtering out staffing agencies or companies you've already applied to. ## `min_salary_usd` (type: `integer`): Minimum annual salary in USD. Jobs without disclosed salary are excluded when this filter is set. ## `max_salary_usd` (type: `integer`): Maximum annual salary in USD. Combine with min\_salary\_usd for a range. ## `posted_after` (type: `string`): Only show jobs posted after this date. Accepts ISO 8601 (e.g. '2026-01-01T00:00:00Z') or relative strings ('7 days ago', '1 month'). ## `page` (type: `integer`): Page number for paginated results. Up to page 20. To explore more jobs, refine your filters (skills, locations, posted date) instead of paging deeper. ## `page_size` (type: `integer`): Number of results per page (max 100). ## `include_company_details` (type: `boolean`): When enabled, replaces the lightweight company preview on each job with the fully enriched company profile (funding, leadership, ratings, tech stack, H1B stats, etc.) fetched from GET /api/companies/{id}. Companies are deduplicated, so each unique company is fetched only once per run. Slower and uses more API calls — leave off if you only need basic company info. ## Actor input object example ```json { "queries": [ "Software Engineer", "Product Manager" ], "locations": [ "San Francisco", "New York", "Remote" ], "page": 1, "page_size": 50, "include_company_details": false } ``` # Actor output Schema ## `jobs` (type: `string`): No description ## `csv_export` (type: `string`): No description # 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 = { "queries": [ "Software Engineer", "Product Manager" ], "locations": [ "San Francisco", "New York", "Remote" ] }; // Run the Actor and wait for it to finish const run = await client.actor("jobo.world/greenhouse-jobs-scraper-api").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 = { "queries": [ "Software Engineer", "Product Manager", ], "locations": [ "San Francisco", "New York", "Remote", ], } # Run the Actor and wait for it to finish run = client.actor("jobo.world/greenhouse-jobs-scraper-api").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 '{ "queries": [ "Software Engineer", "Product Manager" ], "locations": [ "San Francisco", "New York", "Remote" ] }' | apify call jobo.world/greenhouse-jobs-scraper-api --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=jobo.world/greenhouse-jobs-scraper-api", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Greenhouse Jobs Scraper & API", "description": "Scrape jobs directly from Greenhouse ATS via one fast API. Pull live roles from top tech companies like Airbnb, Stripe & Discord. Zero ghost jobs, verified daily — built for job boards, AI agents & tech hiring research.", "version": "2.2", "x-build-id": "jSUDYckYjD1l0mwCZ" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/jobo.world~greenhouse-jobs-scraper-api/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-jobo.world-greenhouse-jobs-scraper-api", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/jobo.world~greenhouse-jobs-scraper-api/runs": { "post": { "operationId": "runs-sync-jobo.world-greenhouse-jobs-scraper-api", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/jobo.world~greenhouse-jobs-scraper-api/run-sync": { "post": { "operationId": "run-sync-jobo.world-greenhouse-jobs-scraper-api", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "properties": { "queries": { "title": "Search Queries", "maxItems": 5, "type": "array", "description": "Job titles or keywords (e.g., 'Software Engineer', 'Backend Developer'). Multiple values are OR-ed. Up to 5 keywords. Adding more rarely improves results — narrow your filters (skills, companies, locations) for better matches.", "items": { "type": "string" } }, "locations": { "title": "Locations", "type": "array", "description": "Cities, regions, or countries (e.g., 'San Francisco', 'United Kingdom'). Geocoded server-side for better matching.", "items": { "type": "string" } }, "work_models": { "title": "Work Model", "type": "array", "description": "Where the work is performed. Leave empty for all.", "items": { "type": "string", "enum": [ "remote", "hybrid", "onsite" ] } }, "employment_types": { "title": "Employment Type", "type": "array", "description": "Filter by employment type. Leave empty for all.", "items": { "type": "string", "enum": [ "full-time", "part-time", "contract", "internship", "freelance", "temporary" ] } }, "experience_levels": { "title": "Experience Level", "type": "array", "description": "Filter by seniority. Leave empty for all.", "items": { "type": "string", "enum": [ "intern", "entry", "mid", "senior", "lead", "executive" ] } }, "skills_include": { "title": "Skills (Include)", "type": "array", "description": "Only return jobs that require ANY of these skills (e.g., 'Python', 'React', 'AWS'). Matched case-insensitively against the AI-extracted qualifications.", "items": { "type": "string" } }, "skills_exclude": { "title": "Skills (Exclude)", "type": "array", "description": "Exclude jobs that require ANY of these skills.", "items": { "type": "string" } }, "companies_include": { "title": "Companies (Include)", "type": "array", "description": "Only return jobs from these specific Greenhouse companies (e.g., 'Stripe', 'Anthropic'). Matched case-insensitively by company name.", "items": { "type": "string" } }, "companies_exclude": { "title": "Companies (Exclude)", "type": "array", "description": "Exclude jobs from these companies. Useful for filtering out staffing agencies or companies you've already applied to.", "items": { "type": "string" } }, "min_salary_usd": { "title": "Minimum Salary (USD)", "minimum": 0, "type": "integer", "description": "Minimum annual salary in USD. Jobs without disclosed salary are excluded when this filter is set." }, "max_salary_usd": { "title": "Maximum Salary (USD)", "minimum": 0, "type": "integer", "description": "Maximum annual salary in USD. Combine with min_salary_usd for a range." }, "posted_after": { "title": "Posted After", "type": "string", "description": "Only show jobs posted after this date. Accepts ISO 8601 (e.g. '2026-01-01T00:00:00Z') or relative strings ('7 days ago', '1 month')." }, "page": { "title": "Page Number", "minimum": 1, "maximum": 20, "type": "integer", "description": "Page number for paginated results. Up to page 20. To explore more jobs, refine your filters (skills, locations, posted date) instead of paging deeper.", "default": 1 }, "page_size": { "title": "Page Size", "minimum": 1, "maximum": 100, "type": "integer", "description": "Number of results per page (max 100).", "default": 50 }, "include_company_details": { "title": "Include full company details", "type": "boolean", "description": "When enabled, replaces the lightweight company preview on each job with the fully enriched company profile (funding, leadership, ratings, tech stack, H1B stats, etc.) fetched from GET /api/companies/{id}. Companies are deduplicated, so each unique company is fetched only once per run. Slower and uses more API calls — leave off if you only need basic company info.", "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 } } } } } } } } } } ```