About the role…
", "company": { "id": 123456, "name": "Example Corp", "domain": "example.com", "employeeCount": 1240, "industry": "Software Development", "countryCode": "US", "funding": { "hasFunding": true, "lastRoundType": "series_c" }, "hq": { "locality": "Austin, TX", "region": "TX" } }, "recruiter": { "kind": "person", "slug": "jane-doe-example", "url": "https://www.linkedin.com/in/jane-doe-example", "fullName": "Jane Doe", "headline": "Technical Recruiter at Example Corp" }, "employerHiring": { "openJobs": 42, "jobs7d": 6, "jobs30d": 19, "jobs90d": 41, "lastPostedAt": "2026-10-21T08:00:00Z", "seniorities30d": [{ "id": 16, "name": "Mid-Senior level", "count": 11 }], "countries30d": ["us"], "topTitles30d": ["Software Engineer", "Account Executive"], "asOf": "2026-10-22T00:00:00Z" } } ``` The `employer…` columns are there when `employerHiring` is on. Free rows say why they are not a result: `no_results` (nothing matched), `invalid` (a company entry that could not be read), `input_problem` (a refused input, with the field named), `no_decision_makers` (an employer with nobody at the chosen roles), `error` (the service could not answer; nothing charged). The **Output tab** has five views: *Overview*, *Company & recruiter*, *Employer hiring*, *Decision makers* and *Preview & breakdown*. ### Decision makers: from a job to the people who hire Turn on `decisionMakers` and every employer in the result is followed by its decision makers, each as a row of its own (`_type: decision_maker`): founders and owners, C-level, VPs and directors, ranked founder + CEO first, assistants and "Office of the CEO" staff removed, each person once per run. Each row carries `fullName`, `jobTitle`, `seniority`, `headline`, `linkedinUrl`, `location`, `forJobId` and `forJobTitle`; the email that reaches the person today rides the row when one is on record and the contact tier is on. - `decisionMakerRoles`: `founder`, `cxo`, `vp`, `director`; default all four. - `decisionMakersPerCompany`: people per employer, in rank order (default 3, maximum 25). - `decisionMakerTitleKeywords`: keep only titles containing any of these words (`sales`, `engineering`, `talent`). C-level acronyms (`cto`, `coo`, `cfo` …) match as whole words, so `cto` finds "Co-Founder & CTO" and not "Director". $3.20 per 1,000 people delivered; an employer with nobody at the chosen roles is a free row. For the same list without the jobs, use [Companies Hiring Now](https://apify.com/b2bsearch/hiring-companies-finder). ### Migrating from another LinkedIn job scraper Your saved input runs as it is: the field names and values are the same. | Their field | Here | |---|---| | `jobTitles`, `locations`, `company`, `employmentType`, `experienceLevel`, `salary`, `under10Applicants`, `postedLimit`, `industryIds` | same names, same values | | `maxItems` | **per run**, not per title and location | | `sortBy`, `page` | accepted and ignored: newest first, the walk pages itself | | `cookie`, `userAgent`, `proxy` | not needed | | `workplaceType` (remote / hybrid / office), `easyApply`, `geoIds` | **not in this database**: a run that sets one stops before anything is charged and names the field | The last line is deliberate. A remote-only run that silently came back with office jobs would be a wrong answer sold as a right one. ### Use Advanced LinkedIn Jobs Scraper with AI agents and MCP This Actor works as a tool for AI agents. Add it to Claude, ChatGPT, Cursor or any other MCP client through the Apify MCP server: ``` https://mcp.apify.com?tools=b2bsearch/linkedin-jobs-scraper ``` The same Actor is a tool in LangChain, CrewAI and the OpenAI Agents SDK, and a step in n8n, Make and Zapier through the Apify integrations. #### What an agent should know before calling it - **When to pick it.** The user wants LinkedIn job postings by job title, location or company, in bulk, with the employer's details and the recruiter. For a database-style search with description keywords, employer size and expired postings, pick [LinkedIn Jobs Database API](https://apify.com/b2bsearch/linkedin-job-search-api) instead. For the list of companies hiring, pick [Companies Hiring Now](https://apify.com/b2bsearch/hiring-companies-finder). - **Minimal input.** `jobTitles` (array) plus `locations` (array with at least one country), or `company` (array). Set `maxItems` to what the user needs; the default is 100. - **Count first.** Send `previewOnly: true` to get the number of matches and their breakdown for free, then decide how many rows to buy. - **Cost.** $0.0008 per `found` job row; rows with any other `_status` are free. Cap a call with `maxTotalChargeUsd` in the run options. - **Read the rows.** `_status` is `found` for a job. A row that is not a result says why in `_status` and `_error`. The useful columns are flat: `title`, `companyName`, `companyDomain`, `locationText`, `postedAt`, `seniorityLevel`, `employmentTypeName`, `salaryText`, `applicantRange`, `recruiterName`, `recruiterUrl`, `url`. - **Small rows.** `compact: true` keeps every plain column and cuts the description to 300 characters. `descriptionType: "none"` drops it. - **Fast.** A small request finishes in seconds, inside one tool call. Input an agent can send as is: ```json { "jobTitles": ["software engineer"], "locations": ["United States"], "postedLimit": "week", "maxItems": 25, "compact": true } ``` #### Example prompts ```text Use b2bsearch/linkedin-jobs-scraper. Count the data engineer jobs posted in Germany in the last week and show the breakdown by seniority and city (preview only), then fetch the 30 newest with their salaries. ``` ```text Use b2bsearch/linkedin-jobs-scraper with company = ["stripe.com", "shopify.com", "atlassian.com"] and postedLimit = "24h". List what each company posted today and who the recruiter is. ``` ```text Use b2bsearch/linkedin-jobs-scraper: account executive jobs in the United Kingdom from the last month, excludeAgencies true, employerHiring true, 100 rows. Rank the employers by how many roles they have open. ``` ```text Use b2bsearch/linkedin-jobs-scraper: "head of talent" OR "talent acquisition lead" in the United States, last week, decisionMakers true with decisionMakerRoles ["founder", "cxo"]. Give me the job, the company and the two people to contact for each. ``` ### FAQ #### How fresh are the jobs? The database holds the last 180 days of postings and is reloaded after each data update, not on a clock. Every row says what the data runs to: `_input.dataAsOf` is the date of the newest posting in the database at the time of your run, and the preview's note repeats it. A job posted in the last hours may not be there yet. Use `postedLimit` or `postedLimitDate` on a schedule to collect what is new since your last run. #### Is this a scraper or an API? Both, in the way that matters: it returns the data a scraper would, through an Actor you can call as an API, from a database we fill and refresh ourselves. Nothing runs against LinkedIn when you press Start, which is why it is fast, needs no cookies and charges nothing for a miss. #### Can I filter remote or hybrid jobs? Not yet: the data carries no remote / hybrid flag, so `workplaceType` is refused rather than faked. A title search for `remote` finds the postings that say so in the title: about 1 in 100 US postings of the last month (27,000 of 2.5 million on 26 October 2026), so treat it as a sample, not as the remote market. #### What does the employer's hiring pace tell me? `employerHiring: true` puts the employer's signal on each job row: how many postings it has open now, how many it posted in the last 7, 30 and 90 days, when it last posted and which titles it posts most. An employer with 40 open roles and 20 posted this month is scaling; one with a single posting is filling a seat. It is free and comes from the same database. #### Are there duplicate jobs? Each posting is one row with its own `jobId`, delivered and charged once per run even when it matches several of your titles. An employer that posts the same role in several cities has several postings, as on the source; deduplicate on `title` + `companyId` for one row per role. #### Does every job have a salary? No. About one posting in seven states one (half in the Netherlands, two in five in China, one in seven in the US). `salaryOnly` keeps just those; `salary` ranges compare the stated pay in the posting's own currency. #### Does every job name a recruiter? About one in nine, and it depends on the country: 28% in India, 17% in the United Kingdom, 7% in the United States. The card is free on every such row; `recruiter: "profile"` adds the full career profile for $3.20 per 1,000 jobs that carry one. #### Why is `maxItems` per run and not per title? Because titles, locations and companies combine into one search: a job matching two of your titles is delivered and charged once, and `maxItems` is a spend cap you can read. Other scrapers run one search per title and location, bill the overlap twice and stop at 1,000 per search; here the walk continues to your cap, up to 10,000. #### How do I get all jobs of a few companies? Put the companies in `company` (page URLs, website domains, slugs or ids) and leave `jobTitles` empty. An employer alone is a complete search. #### Am I charged when nothing is found? No. Empty searches, unusable company entries and refused inputs are free rows with a `_status` and an explanation. Only `found` rows are charged. #### Does it need cookies, a login or an API key? No. The Actor does not sign in to any website and asks for no credentials. ### Related Actors: which one should you use? | Need | Actor | |---|---| | Jobs by title, location and company, in the input names of the best-known scraper | **Advanced LinkedIn Jobs Scraper** (this Actor) | | Database-style job search: description keywords, exclusions, employer size, expired postings, decision makers | [LinkedIn Jobs Database API](https://apify.com/b2bsearch/linkedin-job-search-api) | | The companies hiring for a role, with their hiring pace and decision makers | [Companies Hiring Now](https://apify.com/b2bsearch/hiring-companies-finder) | | Company domain → decision makers | [Decision Maker Email Finder by Domain](https://apify.com/b2bsearch/domain-to-decision-makers) | | Company domain → current employees | [Company Employees](https://apify.com/b2bsearch/company-employees) | | LinkedIn URL → full profile | [Profile Lookup](https://apify.com/b2bsearch/profile-lookup) | | LinkedIn URL → email addresses on record | [LinkedIn Email Finder](https://apify.com/b2bsearch/linkedin-email-finder) | | Filters → list of people | [People Database Search](https://apify.com/b2bsearch/people-database-search) | | Filters → leads with an email | [B2B Leads Finder](https://apify.com/b2bsearch/b2b-leads-finder) | | Filters → list of companies | [Company Database Search](https://apify.com/b2bsearch/company-database-search) | ### Free Apify plan A run started from a free Apify plan delivers the first 100 results and stops; the run's status line says so. Any paid Apify plan lifts the cap. The rows are the same rows a paid run returns. ### Feedback and reviews How did it go? A rating in the **Reviews** tab of this Actor tells the next buyer what to expect; we read every word, good or bad. Got a wrong or stale row? Open the **Issues** tab with the run ID. Issues are public, so leave out emails, phones and names; the run ID is enough for us to find the row. We check every report, fix what is ours to fix and answer in the thread. ### Disclaimer and permitted use **Independent product.** This Actor is an independent tool. It is not affiliated with, endorsed by, or sponsored by LinkedIn Corporation. LinkedIn® is a trademark of its owner. It is named here only to describe the kind of public job postings and profile links this Actor returns. **No platform access.** This Actor does not log in to, crawl or collect pages from LinkedIn or any other service. Every answer comes from our own database of job postings and business-contact records. It never returns passwords, messages, or content from non-public accounts. **Permitted use.** Business purposes only: job market research, recruiting, sales prospecting, CRM enrichment and building job feeds. You may not use this Actor or its output to: - stalk, harass, threaten, dox or publicly expose any person; - decide on anyone's eligibility for credit, employment, housing or insurance. This Actor is not a consumer reporting agency and its output is not a consumer report under the U.S. Fair Credit Reporting Act; - send unsolicited bulk messages, or place autodialed or prerecorded calls or texts without the consent the law requires; - profile people by health, religion, political opinion, sexual orientation, ethnicity or union membership; - build or resell a contact database from the results. **Your responsibilities.** You decide what to search for and what to do with the result. You are responsible for having a lawful basis for that use and for complying with the laws that apply to you, including GDPR and UK GDPR, ePrivacy and PECR, CCPA/CPRA, CAN-SPAM, and the TCPA and Do Not Call rules. Honor every opt-out you receive. **Removal requests.** To have a person's data removed, open an issue on this Actor with only the profile link. Nothing else is needed, and the record is removed from every listing. **Accuracy.** Records can be incomplete or out of date. Output is provided as is. Check before you rely on it. # Actor input Schema ## `jobTitles` (type: `array`): Job titles to look for, one per line; a job whose title contains any line is kept. Whole words, any case. A line may use boolean search: AND, OR, NOT, "exact phrase", parentheses (for example: (backend OR platform) engineer NOT intern). Up to 10 lines. Example values: software engineer, data engineer. ## `locations` (type: `array`): Where the job is: countries by name or two-letter code (United States, Germany, gb, UK), US states (California), cities (Berlin; Austin, Texas). Any of them. A search needs at least one country or a company; a city or a title alone is not enough. Up to 60. ## `maxItems` (type: `integer`): How many jobs to deliver in this run, across all titles and locations together (default 100; 0 = up to 10,000). This is your spend cap: $0.80 per 1,000 jobs delivered. Free Apify plan: up to 100. ## `previewOnly` (type: `boolean`): Returns how many jobs match and their breakdown by country, seniority, employment type, industry, top employers, titles and cities. No job rows, no charge. Run it first to size a search, then turn it off to get the jobs. ## `compact` (type: `boolean`): Returns a short row: every plain column, long text (the description) cut to 300 characters, nested blocks left out. Made for AI agents and LLM pipelines with a context limit. Same price. Off by default. ## `company` (type: `array`): Only jobs at these employers: company page URL, page slug, website domain (stripe.com), numeric id or a company name (matched as part of the name). A company list alone is a complete search. Up to 100. ## `postedLimit` (type: `string`): Only jobs posted within this window, counted from the start of the run. The database keeps 180 days of postings and is reloaded after each data update; every row says what date the data runs to. ## `experienceLevel` (type: `array`): Keep these seniority levels, as the posting states them. Any of them. ## `employmentType` (type: `array`): Keep these employment types. Any of them. ## `industryIds` (type: `array`): Only jobs in these industries, by name (Software Development, Hospitals and Health Care) or by numeric industry id (4 for Software Development). An industry covers its sub-industries. Up to 30. ## `salary` (type: `array`): Yearly salary ranges, one per line: 100k+, 60k-80k or 100000-150000. Keeps postings whose stated pay reaches the lowest floor (and stays under the highest ceiling when every line has one). Postings without a stated salary never match: about one in seven states one. ## `salaryCurrency` (type: `string`): Three-letter code the salary ranges are in (default USD). A posting is compared in its own currency. ## `salaryOnly` (type: `boolean`): Keep only postings that state a salary (about one in seven overall; half in the Netherlands, two in five in China). ## `under10Applicants` (type: `boolean`): Keep postings in the lowest applicant bucket, fewer than 25 applicants. The data keeps applicant counts in buckets of 25, so this is the closest honest answer to "under 10". ## `excludeAgencies` (type: `boolean`): Drops postings by staffing and recruiting firms and job-board aggregators (by the posting's industry and by the employer's own card), and employers with far more postings than employees (at least 200 open, or 100 posted in 30 days, and more than two per employee). Off by default so the search reads like the source. ## `postedLimitDate` (type: `string`): Only jobs posted on or after this date (YYYY-MM-DD). With "Posted in the last" too, the later of the two wins. Set it to your last run's date for a daily feed. ## `recruiter` (type: `string`): "card" (default, free): name, headline and profile URL of the recruiter when the posting names one (about one posting in nine; 28% in India, 17% in the UK, 7% in the US). "profile": their full career profile, $3.20 per 1,000 jobs that carry one. "none": leave the recruiter out. ## `employerHiring` (type: `boolean`): Adds the employer's hiring signal to each job row, free: open postings now, postings in the last 7, 30 and 90 days, the date of its latest posting and its top titles of the last 30 days (employerOpenJobs, employerJobs7d/30d/90d, employerLastPostedAt, employerTopTitles30d). Tells a company scaling a team from one that posted once. ## `decisionMakers` (type: `boolean`): After each job, adds the founders, C-level, VPs and directors of its employer as separate rows (each employer once per run): name, title, seniority, headline, profile URL, location, and the email on record when the contact tier is on. $3.20 per 1,000 people delivered; employers with nobody on record are free. ## `decisionMakerRoles` (type: `array`): Which levels count as a decision maker. Rows are ordered founder + CEO first, then other founders and CEOs, the rest of the C-level, VPs, directors. Default: all four. ## `decisionMakersPerCompany` (type: `integer`): How many people to add per employer, in rank order (default 3, maximum 25). Your spend cap per employer: $0.0032 per person. ## `decisionMakerTitleKeywords` (type: `array`): Keep only decision makers whose job title contains any of these words, for example sales, engineering, talent (3-64 characters each, up to 10). ## `descriptionType` (type: `string`): What the description column carries: plain text and HTML (default), text only, HTML only, or none for small rows. Same price. ## `sortBy` (type: `string`): Accepted for compatibility with other job scrapers' saved inputs; jobs are always delivered newest first. ## Actor input object example ```json { "jobTitles": [ "software engineer" ], "locations": [ "United States" ], "maxItems": 25, "previewOnly": false, "compact": false, "postedLimit": "any", "salaryCurrency": "USD", "salaryOnly": false, "under10Applicants": false, "excludeAgencies": false, "recruiter": "card", "employerHiring": false, "decisionMakers": false, "decisionMakersPerCompany": 3, "descriptionType": "both" } ``` # 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 '