The job object

Field names follow common job-feed conventions, so most integrations map directly.

Field	Type	Meaning
`id`	string	Stable id: vendor:tenant:source_job_id
`title`	string	Job title
`organization`	string	Company name
`apply_url, url`	string	The employer’s application page
`source`	string	workday, greenhouse, lever, ashby …
`date_posted, date_first_seen`	date	Freshness filters use posted, else first seen
`locations_derived, cities_derived, regions_derived, countries_derived`	string[]	Where the job is
`remote_friendly`	boolean	The posting mentions remote, hybrid or work from home
`ai_experience_level`	string \| null	0-2, 2-5, 5-10, 10+ or not stated
`ai_employment_type`	string[]	FULL_TIME, PART_TIME, CONTRACTOR, TEMPORARY, INTERN
`has_salary`	boolean	The employer published pay
`ai_salary_min_value, ai_salary_max_value`	number \| null	Published pay, annualized
`ai_salary_currency, ai_salary_unit_text`	string \| null	Currency; unit is YEAR after annualizing
`estimated_pay`	object	A model estimate for display. Never used by filters
`org_linkedin_industry, org_linkedin_size`	string \| null	Company industry and headcount bucket, where matched
`organization_url, organization_logo, org_linkedin_slug`	string \| null	Company website, logo and LinkedIn slug
`ai_key_skills`	string[]	Skills named in the posting
`department, seniority`	string \| null	As stated by the employer
`requisition_id`	string \| null	The employer’s own job number
`last_seen_at`	date	When we last saw the posting live
`salary_period`	string \| null	The pay period the employer published
`description_text, ai_requirements_summary, ai_core_responsibilities`	string	Full text (full job, or include_description=true)
`job_function, job_language`	string \| null	Job function and posting language (full job)
`ai_flags`	object	Model-read yes/no facts: is_senior, has_equity, degree_required, travel_required… Display only; may be wrong
`company`	object \| null	Full company profile (full job, or include_company=true)

Example response

json

{
  "id": "greenhouse:acmecloud:7234001",
  "title": "Senior Data Engineer",
  "organization": "Acme Cloud",
  "organization_url": "https://acme.example",
  "organization_logo": "https://…/logo.png",
  "org_linkedin_industry": "Software Development",
  "org_linkedin_size": "1001-5000",
  "url": "https://boards.greenhouse.io/acmecloud/jobs/7234001",
  "apply_url": "https://boards.greenhouse.io/acmecloud/jobs/7234001",
  "source": "greenhouse",
  "date_posted": "2026-09-26",
  "date_first_seen": "2026-09-27",
  "locations_derived": ["Remote, United States"],
  "countries_derived": ["US"],
  "remote_friendly": true,
  "ai_experience_level": "5-10",
  "ai_employment_type": ["FULL_TIME"],
  "has_salary": true,
  "ai_salary_min_value": 170000,
  "ai_salary_max_value": 210000,
  "ai_salary_currency": "USD",
  "ai_salary_unit_text": "YEAR",
  "ai_key_skills": ["Python", "SQL", "Spark", "Airflow"]
}