# IT Job Intelligence (`fluxcurulin/it-job-intelligence`) Actor Aggregate IT and cloud job postings with skills, tools, location, salary ranges, remote flags, and posting dates. Extract structured market intelligence for recruiting teams, compensation analysts, and IT workforce planners tracking tech hiring trends. - **URL**: https://apify.com/fluxcurulin/it-job-intelligence.md - **Developed by:** [Josh Pinkerton](https://apify.com/fluxcurulin) (community) - **Categories:** AI, Agents, Automation - **Stats:** 0 total users, 0 monthly users, 0.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## 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 ## it-job-intelligence Aggregate IT and cloud job postings from public search pages and extract structured skills snapshots to stay ahead of hiring trends. ### Personas #### B2B Talent acquisition leaders, workforce planning managers, HR-tech platforms, and corporate sourcing teams use this actor to benchmark emerging skill demand across cities and remote markets. If you're refreshing your engineering competency framework or pricing contract roles, the structured skills snapshot removes the manual scrape-and-parse step. #### B2C Job seekers, career coaches, indie recruiters, and civic-tech/open-data researchers use this actor to track what frameworks and tools are actually required in the wild right now. If you're building your third portfolio project or auditing which cloud certs are "in" for 2026, real posting data beats opinion every time. ### What it does - Crawls listing pages from public job search endpoints (**Indeed**, **Dice**, **LinkedIn public URL pattern**) - Extracts structured fields: title, company, location, salary range, remote flag, posted date, direct URL - Enqueues detail links when available and normalizes overlapping fields - Emits: - `job_posting` — one row per parsed job - `skills_snapshot` — one per listing/detail page with aggregated tool counts ### Model | Event | Price | |---|---| | `job_posting` | $0.06 | | `skills_snapshot` | $0.12 | ### Example input ```json { "searchQuery": "cloud engineer", "location": "United States", "maxJobs": 50, "maxPages": 3, "urls": [ { "url": "https://www.indeed.com/jobs?q=cloud+engineer&l=United+States" }, { "url": "https://www.dice.com/jobs?q=cloud+engineer&l=United+States" } ] } ```` ### Notes - Configure `urls` to point search pages or allow the actor to build them from `searchQuery` + `location`. - Public search pages change layout often; retarget extraction with CSS selectors if a source redesigns. - LinkedIn public search URLs require a logged-out profile; use responsibly and respect `robots.txt`. # Actor input Schema ## `searchQuery` (type: `string`): Job search keywords, e.g. 'cloud engineer' or 'site reliability engineer'. ## `location` (type: `string`): Location filter for job search, e.g. 'United States' or 'Remote'. ## `maxJobs` (type: `integer`): Maximum number of job postings to extract. ## `maxPages` (type: `integer`): Maximum number of pagination pages to follow. ## `urls` (type: `array`): Listing/detail page URLs to crawl. If empty, the actor can construct search URLs from searchQuery and location. ## Actor input object example ```json { "maxJobs": 50, "maxPages": 3, "urls": [ { "url": "https://www.indeed.com/jobs?q=cloud+engineer&l=United+States" } ] } ``` # Actor output Schema ## `results` (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 = { "urls": [ { "url": "https://www.indeed.com/jobs?q=cloud+engineer&l=United+States" } ] }; // Run the Actor and wait for it to finish const run = await client.actor("fluxcurulin/it-job-intelligence").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 = { "urls": [{ "url": "https://www.indeed.com/jobs?q=cloud+engineer&l=United+States" }] } # Run the Actor and wait for it to finish run = client.actor("fluxcurulin/it-job-intelligence").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 '{ "urls": [ { "url": "https://www.indeed.com/jobs?q=cloud+engineer&l=United+States" } ] }' | apify call fluxcurulin/it-job-intelligence --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=fluxcurulin/it-job-intelligence", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "IT Job Intelligence", "description": "Aggregate IT and cloud job postings with skills, tools, location, salary ranges, remote flags, and posting dates. Extract structured market intelligence for recruiting teams, compensation analysts, and IT workforce planners tracking tech hiring trends.", "version": "1.0", "x-build-id": "UwK4ce146oIRKhhTg" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/fluxcurulin~it-job-intelligence/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-fluxcurulin-it-job-intelligence", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/fluxcurulin~it-job-intelligence/runs": { "post": { "operationId": "runs-sync-fluxcurulin-it-job-intelligence", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/fluxcurulin~it-job-intelligence/run-sync": { "post": { "operationId": "run-sync-fluxcurulin-it-job-intelligence", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "searchQuery", "location" ], "properties": { "searchQuery": { "title": "Search query", "type": "string", "description": "Job search keywords, e.g. 'cloud engineer' or 'site reliability engineer'." }, "location": { "title": "Location", "type": "string", "description": "Location filter for job search, e.g. 'United States' or 'Remote'." }, "maxJobs": { "title": "Max jobs", "type": "integer", "description": "Maximum number of job postings to extract.", "default": 50 }, "maxPages": { "title": "Max pages", "type": "integer", "description": "Maximum number of pagination pages to follow.", "default": 3 }, "urls": { "title": "Start URLs", "type": "array", "description": "Listing/detail page URLs to crawl. If empty, the actor can construct search URLs from searchQuery and location.", "default": [], "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } } } }, "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 } } } } } } } } } } ```