LinkedIn Job Details Scraper
Pricing
from $3.30 / 1,000 successful api calls
Extract structured details from a LinkedIn job posting, including title, company, and requirements. For recruiting and market research.
You can access the LinkedIn Job Details Scraper programmatically from your own applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, you’ll need an Apify account and your API token, found in Integrations settings in Apify Console.
{ "openapi": "3.0.1", "info": { "version": "0.0", "x-build-id": "4PcfN3QEjY6JrEy2g" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/automationagents~linkedin-job-details-export/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-automationagents-linkedin-job-details-export", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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/automationagents~linkedin-job-details-export/runs": { "post": { "operationId": "runs-sync-automationagents-linkedin-job-details-export", "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/automationagents~linkedin-job-details-export/run-sync": { "post": { "operationId": "run-sync-automationagents-linkedin-job-details-export", "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": [ "JSESSIONID", "User-Agent", "X-Restli-Protocol-Version", "bcookie", "bscookie", "csrf-token", "liJobUrl", "li_at", "li_theme", "li_theme_set", "liap", "profileId", "proxy", "timezone", "timezoneOffset", "txSmSelfProfileUrl", "user-agent", "x-li-lang", "x-li-track" ], "properties": { "liJobUrl": { "title": "liJobUrl", "type": "string", "description": "LinkedIn job posting URL to fetch details for." }, "li_at": { "title": "li_at", "type": "string", "description": "LinkedIn session cookie used for authenticated requests." }, "JSESSIONID": { "title": "JSESSIONID", "type": "string", "description": "LinkedIn JSESSIONID cookie value from your authenticated browser session." }, "bcookie": { "title": "bcookie", "type": "string", "description": "LinkedIn browser identification cookie." }, "liap": { "title": "liap", "type": "string", "description": "LinkedIn account cookie used by the authenticated session." }, "li_theme_set": { "title": "li_theme_set", "type": "string", "description": "Theme preference cookie captured from the same browser session." }, "li_theme": { "title": "li_theme", "type": "string", "description": "LinkedIn theme cookie from the authenticated browser session." }, "timezone": { "title": "timezone", "type": "string", "description": "Browser timezone string, for example Asia/Kolkata or America/New_York." }, "bscookie": { "title": "bscookie", "type": "string", "description": "LinkedIn secure browser cookie used together with other session cookies." }, "user-agent": { "title": "user-agent", "type": "string", "description": "Lowercase user-agent header value from the browser session." }, "timezoneOffset": { "title": "timezoneOffset", "type": "string", "description": "Browser timezone offset value captured from the logged-in session, such as 5.5 or -4." }, "csrf-token": { "title": "csrf-token", "type": "string", "description": "CSRF token used for authenticated LinkedIn requests." }, "profileId": { "title": "profileId", "type": "string", "description": "LinkedIn profile identifier or public profile slug associated with the authenticated account." }, "User-Agent": { "title": "User-Agent", "type": "string", "description": "Standard User-Agent header value from the same authenticated browser session." }, "x-li-track": { "title": "x-li-track", "type": "string", "description": "LinkedIn tracking header value captured from browser network requests." }, "x-li-lang": { "title": "x-li-lang", "type": "string", "description": "LinkedIn language header, usually a locale such as en_US." }, "X-Restli-Protocol-Version": { "title": "X-Restli-Protocol-Version", "type": "string", "description": "LinkedIn Rest.li protocol version header, usually 2.0.0." }, "txSmSelfProfileUrl": { "title": "txSmSelfProfileUrl", "type": "string", "description": "Your own LinkedIn profile URL from the same logged-in session." }, "proxy": { "title": "proxy", "type": "object", "description": "Proxy configuration object passed to the backend. For this actor the common fields are ip, port, username, and password." } } }, "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 } } } } } } } } }}OpenAPI is a standard for designing and describing RESTful APIs, allowing developers to define API structure, endpoints, and data formats in a machine-readable way. It simplifies API development, integration, and documentation.
OpenAPI is effective when used with AI agents and GPTs by standardizing how these systems interact with various APIs, for reliable integrations and efficient communication.
By defining machine-readable API specifications, OpenAPI allows AI models like GPTs to understand and use varied data sources, improving accuracy. This accelerates development, reduces errors, and provides context-aware responses, making OpenAPI a core component for AI applications.
You can download the OpenAPI definitions for LinkedIn Job Details Scraper from the options below:
If you’d like to learn more about how OpenAPI powers GPTs, read our blog post.
You can also check out our other API clients: