LinkedIn Company Employees Scraper — Find people who work at any company

Find LinkedIn profiles of people who self-identify their employer in their headline — the way most LinkedIn users do. Clean structured JSON output. No LinkedIn login, no cookies, no browser session, no account ban risk.

Built for B2B sales prospecting at named accounts, recruiting target-company outreach lists, competitive talent intelligence, ABM contact-discovery, and investor portfolio-company research.

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Honest scope: who this catches and who it misses

Most LinkedIn-employees scrapers claim to return "the full employee list" of a company. Truthfully — that requires either a logged-in scrape (account ban risk) or a paid LinkedIn Premium / Sales Navigator integration. Neither is cookieless.

This actor takes a different approach: it finds employees who publicly self-identify their employer in their LinkedIn headline (e.g., "Senior Engineer at Microsoft", "Microsoft Architect", "@ Microsoft"). That's how most professionals format their headlines — so for famous companies this finds the majority of public-facing employees.

Approach	Coverage	Trade-off
Logged-in scrape	~100% (full list)	Account ban risk, requires cookie, brittle
This actor (headline match)	40-70% for famous companies	Cookieless, safe, $1/1k
Paid LinkedIn Sales Navigator API	~100%	$$$ + corporate-only access

Best for: famous distinctive company names (Microsoft, OpenAI, Apple, Stripe). Less effective for: ambiguous names ("Apple" matches fruit-related profiles too) or small companies where few employees write their employer in their headline.

What you get — 1 record per matching employee

For each company you provide, the actor:

1. Resolves the company slug → canonical name + ID via /companies/company/universal-name-to-id + /companies/company/info-v2
2. Searches /search/people with the company name as keyword
3. Filters results client-side: emit only people whose headline contains the company name (case-insensitive)
4. Excludes "Ex-", "Former", "Previously at" entries client-side
5. Emits a companyEmployee record per match

companyEmployee record (16 fields)

• Company back-refs: companyId, companyName, companyUniversalName, companyLinkedinUrl
• Identity: fullName, firstName, lastName, profileId, profileUrn, profileUrl
• Public bio: headline, location, isPremium, profilePictureUrl
• Tracking: sourceInput, scrapedAt

Plus diagnostic (1 per zero-match company) and summary (1 per run).

Use cases (top 7)

1. B2B sales — find decision-makers at target accounts

Feed your top-100 accounts as companyUrls. Add a roleFilter like "VP Sales" or "Head of Marketing". Get an instant prospect list with profile URLs ready for personalized outreach.

2. Recruiting — competitor talent extraction

Need to recruit data scientists from OpenAI? Feed openai + roleFilter: "Data Scientist". You get a list of public-facing OpenAI data scientists in seconds.

3. Competitive intelligence — see who's hiring whom

Track a competitor's headcount-by-LinkedIn-headline over time. New senior hires show up in your monthly cron job. Departures show up as headline changes.

4. ABM (account-based marketing) — multi-contact targeting

For each target account, get the public buying-committee members (CMO, CRO, COO, CISO). Pipe into your ABM tool for coordinated multi-touch outreach.

5. Investor research — portfolio-company team mapping

Map the public-facing teams of your portfolio companies. Useful for board-meeting prep, BD intros, and tracking team growth quarter-over-quarter.

6. Conference / event organizer — speaker bench-building

Need speakers from a specific company? Feed the company URL + role-filter for "Director" or above. Returns potential keynote candidates in seconds.

7. Customer success — relationship-mapping at customer accounts

Map every public LinkedIn-visible person at your top customer accounts. Detect when key contacts change roles or leave (headline updates) so you can trigger your offboarding/transition playbooks.

How it works

1. Set companyUrls — LinkedIn company URLs (or slugs). Schools and showcase pages also supported.
2. Set maxEmployeesPerCompany (1-1000, default 100).
3. Optionally set roleFilter (e.g., "Software Engineer", "CEO") — passes through to vendor's title filter.
4. Optionally set aliases (comma-separated) — alternate names that might appear in headlines (e.g., "MSFT, Azure" for Microsoft).

For each company: resolve slug → canonical name → search → client-filter on headline → emit matches.

Cost-control: customer pays only for MATCHED records, not the candidates scanned. We scan up to 1000 candidates per company at no extra charge; you pay $1/1k for the matches.

No login required. No cookies. Cookieless via managed vendor partnership — no account ban risk.

Example input

{
  "companyUrls": [
    "https://www.linkedin.com/company/microsoft/",
    "openai",
    "anthropic"
  ],
  "maxEmployeesPerCompany": 100,
  "roleFilter": "Software Engineer"
}

This returns up to 300 employee records (100 × 3 companies) of software engineers who self-identify these companies in their headlines.

Pricing — pay only for matched results

$1.00 per 1,000 matched employees. Pay-per-result.

• ✅ No subscription
• ✅ No charge for scanned-but-not-matched candidates (we scan up to 1000 per company at no cost)
• ✅ No charge for companies with zero matches (clean diagnostic record)
• ✅ Apify's free tier ($5/month platform credit) covers ~5,000 matched records to start

Cost comparison: build a 10,000-employee prospect list (across 100 target accounts × 100 employees each):

Approach	Cost
LinkedIn Sales Navigator (enterprise tier)	~$1,500+/month
harvestapi people search (no company filter)	$20+ (post-filter manually)
This actor	$10 (one-shot, cookieless)

Combine with other LinkedIn actors

Build a complete LinkedIn-account-intelligence pipeline:

1. This actor → find public-headline employees at named accounts
2. LinkedIn Profile Scraper (a17) → pipe profileUrl for full firmographic enrichment per employee
3. LinkedIn Post Scraper (a16) → pull each employee's recent post activity (engagement signals)
4. LinkedIn Profile Reactions Scraper (a9) → see what each employee reacts to (interest signals)
5. LinkedIn Company Scraper (a11) → pull full firmographics on the target companies

FAQ

Q: Why don't all Microsoft employees appear? Many people don't put their employer in their LinkedIn headline (e.g., "Senior PM" without "at Microsoft"). Our cookieless approach catches the ones who do — typically 40-70% of public-facing employees at famous companies. For 100% coverage you'd need a logged-in scrape, which has account-ban risk and breaks our "no cookies" principle.

Q: What about ex-employees showing "Ex-Microsoft" in their headline? Filtered out automatically. We exclude common patterns: "ex-X", "ex X", "former X", "formerly X", "previously X", "prev X", "past X".

Q: My company name has multiple spellings or variants? Use the aliases input — comma-separated list of alternate names. Example: "MSFT, Azure" for Microsoft. Any of those appearing in a headline counts as a match.

Q: Can I filter by role / job title? Yes. Use roleFilter (e.g., "VP Engineering", "Head of Sales"). This passes through to the vendor's title filter to narrow the search.

Q: How accurate is the match? We exclude obvious ex-employees but include all current-employee headlines that mention the company. For ambiguous company names (Apple → fruit-related profiles), you may get false positives. Use aliases defensively for these cases.

Q: Can I get the full LinkedIn employees-list of a company? No cookieless scraper can. LinkedIn auth-gates the full employees-list page. Our approach trades comprehensiveness for safety (no account-ban risk).

Q: Is this safe to use vs my LinkedIn account? Yes. No login, no cookies, no browser session. The actor never authenticates as you.

Privacy & compliance

This actor surfaces publicly self-identified employer information from LinkedIn profile headlines — content that any logged-out visitor can read.

LinkedIn user data may be subject to LinkedIn's Terms of Use and applicable data protection laws (GDPR, CCPA, etc.). Customers are responsible for compliance when processing or contacting scraped individuals, especially for outreach (CAN-SPAM, GDPR Article 6, etc.).

Not affiliated with, endorsed by, or sponsored by LinkedIn Corporation or Microsoft Corporation.