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POST
https://api.gtmapis.com
/
v1
/
linkedin
/
hires
LinkedIn Recent Hires
curl --request POST \
  --url https://api.gtmapis.com/v1/linkedin/hires \
  --header 'Content-Type: application/json' \
  --header 'X-API-Key: <api-key>' \
  --data '
{
  "domain": "<string>",
  "linkedin_url": "<string>",
  "days_back": 123,
  "limit": 123
}
'
{
  "domain": "<string>",
  "company_name": "<string>",
  "recent_hires": [
    {}
  ],
  "total": 123,
  "days_back": 123,
  "hiring_velocity": 123,
  "top_departments": [
    {}
  ],
  "department_breakdown": {}
}

LinkedIn Recent Hires

Discover who a company has recently hired. Use this to identify buying signals - companies that are growing often have budget to spend.

Endpoint

POST /v1/linkedin/hires

Request

domain
string
required
Company domain (e.g., “stripe.com”)
linkedin_url
string
LinkedIn company URL (alternative to domain)
days_back
integer
default:"90"
How many days back to look for hires (max 180)
limit
integer
default:"20"
Max number of hires to return (max 100)

Example Request

curl -X POST https://api.gtmapis.com/v1/linkedin/hires \
  -H "Content-Type: application/json" \
  -H "X-API-Key: gtm_test_your_key_here" \
  -d '{
    "domain": "stripe.com",
    "days_back": 90,
    "limit": 20
  }'

Response

domain
string
Company domain
company_name
string
Company name
recent_hires
array
List of recently hired employees
total
integer
Total number of hires found
days_back
integer
Number of days searched
hiring_velocity
number
Average hires per month
top_departments
array
Departments with most hires
department_breakdown
object
Hires count by department

Example Response

{
  "domain": "stripe.com",
  "company_name": "Stripe",
  "recent_hires": [
    {
      "first_name": "Emily",
      "last_name": "Rodriguez",
      "full_name": "Emily Rodriguez",
      "title": "Senior Product Manager",
      "seniority": "Senior",
      "department": "Product",
      "linkedin_url": "https://linkedin.com/in/emilyrodriguez",
      "location": "San Francisco, CA",
      "start_date": "2026-01-10"
    },
    {
      "first_name": "David",
      "last_name": "Kim",
      "full_name": "David Kim",
      "title": "Staff Engineer",
      "seniority": "Senior",
      "department": "Engineering",
      "linkedin_url": "https://linkedin.com/in/davidkim",
      "location": "Seattle, WA",
      "start_date": "2026-01-05"
    }
  ],
  "total": 45,
  "days_back": 90,
  "hiring_velocity": 15.0,
  "top_departments": ["Engineering", "Sales", "Product"],
  "department_breakdown": {
    "Engineering": 20,
    "Sales": 12,
    "Product": 8,
    "Marketing": 5
  },
  "source_provider": "proxycurl",
  "credits_charged": 2,
  "latency_ms": 1456,
  "cache_hit": false
}

Hiring Signals

The response includes valuable sales signals:
SignalWhat It Means
High hiring_velocityCompany is growing fast, likely has budget
Engineering in top departmentsProduct investment, may need dev tools
Sales in top departmentsRevenue focus, may need sales tools
Marketing in top departmentsGrowth focus, may need marketing tools
Senior-level hiresBuilding leadership, major initiatives

Credit Pricing

ScenarioCredits Charged
Fresh lookup2 credits
Cache hit (within 24 hours)0 credits
Error / company not found0 credits
Recent hires data is cached for 24 hours since it changes frequently.

Use Cases

New hires often have budget and mandate to buy tools. They’re great prospects in their first 90 days.
High hiring velocity indicates growth and budget availability.
If you sell to engineering teams, look for companies hiring lots of engineers.
Track which departments your competitors are investing in.