Built In Jobs Scraper — Hiring Intelligence Feed

What is Built In Jobs Scraper — Hiring Intelligence Feed?

Built In Jobs Scraper extracts technology and startup job listings from Built In search pages and company job boards into a structured dataset. Each row is one job with its title, Built In job URL and ID, and, with job details on, the hiring company, location, workplace type, employment type, experience level, salary range, skills, description, posting dates and direct apply link. Recruiters, compensation analysts, founders tracking competitor hiring and AI agents use it to turn Built In listings into a feed they can filter, compare and schedule.

Why teams use it

• Two depths in one Actor. A fast card-level feed with includeJobDetails: false, or full job pages with salary, skills, dates and applyUrl when it is true.
• Normalized salary. salaryMin, salaryMax, salaryCurrency and salaryPeriod are numeric and unit-labelled when Built In publishes pay.
• Agent-friendly descriptions. responseFormat: "concise" keeps descriptions short; detailed returns the longer text.
• Exact saved searches. Paste any Built In jobs, category or company-jobs URL into startUrls.
• Stable shape. Every row has the same keys, with skills always an array, which keeps CSV exports and databases tidy.

Best fit for this Actor

• Designed for public Built In job listings, from a role keyword search to a specific company's jobs page.
• Best fit for hiring intelligence, salary-band research, job-alert pipelines and recruiter sourcing of companies that are hiring.
• To compare the same role on a second tech job board, use Dice.com Jobs Scraper with the same keyword and merge the two datasets.
• When you want a company's full open roles straight from its career site, continue with Career Site Job Listing Scraper for the companies you find here.

Example workflow: competitor hiring watch

A startup founder wants to know how fast three competitors are hiring machine-learning talent. He starts with searchQuery set to machine learning engineer, workplaceType set to remote, maxResults at 50 and includeJobDetails on. The dataset returns each role's company, salary range, skills and posting date. He filters to the three competitor names, compares their salary bands with his own offer, then schedules the run weekly and exports new rows into a hiring dashboard so changes in competitor demand show up early.

Input

{
  "searchQuery": "machine learning engineer",
  "location": "Austin, TX",
  "workplaceType": "hybrid",
  "maxResults": 20,
  "includeJobDetails": true,
  "responseFormat": "concise"
}

To scrape an existing Built In results page exactly:

{
  "startUrls": [{ "url": "https://builtin.com/jobs?search=ai" }],
  "maxResults": 10,
  "includeJobDetails": true
}

Field	Type	What it controls
searchQuery	string	Role or skill phrase such as product manager. Default software engineer.
location	string	Optional city and state such as Austin, TX. Empty means all locations.
workplaceType	string	any (default), remote, hybrid or office.
startUrls	array	Built In jobs, category or company-jobs page URLs to scrape exactly.
maxResults	integer	Jobs returned and billed across the run, 1 to 100. Default 20.
includeJobDetails	boolean	Visit each job page for company, salary, skills, dates, description and apply URL. Default true.
responseFormat	string	concise (default) for a short description or detailed for the longer text.

Output

One dataset row per job.

Field	What it contains
jobId, title, jobUrl	Built In job ID, role title and listing URL
companyName	Hiring company, from the job page
location, workplaceType, employmentType	Location, remote/hybrid/office arrangement and type such as FULL_TIME
experienceLevel	Seniority shown or inferred from the title
salaryMin, salaryMax, salaryCurrency, salaryPeriod	Published pay range, currency and unit
skills	Deduplicated skills and technologies
description	Plain-text description, length set by responseFormat
postedAt, validThrough	Posting and expiry dates when published
applyUrl	Direct employer application link when available
scrapedAt, source	Collection time and source site

Fields from the job page fill in when includeJobDetails is on and Built In publishes them; otherwise they are null. A quick card-level row looks like this:

{
  "jobId": "11452578",
  "title": "AI Associate Engineer for Sales Assistant Platform Technology - Software Engineer III",
  "companyName": null,
  "location": null,
  "workplaceType": null,
  "employmentType": null,
  "experienceLevel": null,
  "salaryMin": null,
  "salaryMax": null,
  "salaryCurrency": null,
  "salaryPeriod": null,
  "skills": [],
  "description": null,
  "postedAt": null,
  "validThrough": null,
  "jobUrl": "https://builtin.com/job/ai-associate-engineer-sales-assistant-platform-technology-software-engineer-iii/11452578",
  "applyUrl": null,
  "scrapedAt": "2026-10-01T01:29:36.031Z",
  "source": "builtin.com"
}

Every run also writes OUTPUT and RUN_SUMMARY to the default key-value store, including the run outcome (for example COMPLETE or VALID_EMPTY for a valid search with no matches).

Pricing

This Actor uses Pay per event plus Apify platform usage. The events are:

• Actor Start, once per run.
• Job scraped, once for each complete, validated job row saved to the dataset.

Worked example: a search with maxResults set to 20 that saves 20 jobs costs one Actor Start event plus 20 Job scraped events, plus the compute and proxy usage of the run. Job detail pages take more browser time, so a card-level run with includeJobDetails: false uses less platform usage. Check the live Pricing tab on this page for current event prices.

API example

curl -X POST "https://api.apify.com/v2/acts/khadinakbar~built-in-jobs-scraper/run-sync-get-dataset-items?token=YOUR_API_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"searchQuery": "data engineer", "workplaceType": "remote", "maxResults": 10, "includeJobDetails": true}'

from apify_client import ApifyClient

client = ApifyClient("YOUR_API_TOKEN")
run = client.actor("khadinakbar/built-in-jobs-scraper").call(
    run_input={"searchQuery": "data engineer", "workplaceType": "remote", "maxResults": 10}
)
for job in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(job["title"], job.get("companyName"), job.get("salaryMin"), job["jobUrl"])

Use it with AI agents (MCP)

Connect the Actor to Claude, ChatGPT, Cursor or another MCP client through Apify MCP, then ask:

Find 15 remote data engineer jobs on Built In with full job details. Return company, salary range, top skills and apply link, and tell me the median published salary.

The agent receives job rows with salary, skills and links, reads them with get-dataset-items, and can cite jobUrl and scrapedAt as provenance. responseFormat: "concise" keeps descriptions compact for the agent's context. Cost scales with saved jobs, so maxResults keeps agent runs scoped.

Best results

Starting situation	Helpful action	Expected outcome
You need salary and skills	Keep includeJobDetails: true	Rows with pay range, skills, dates and apply link
You need a fast list of open roles	Set includeJobDetails: false	Quick title and job URL feed for a first pass
A saved Built In search or company page	Paste its URL in startUrls	Exactly the listings you see on Built In
Remote-only research	Set workplaceType to remote	Remote roles only
Ongoing monitoring	Schedule a focused query with the same maxResults	Comparable runs week to week

Builder's note

I built this for people who ask hiring questions, such as who is paying what for which skills, rather than people browsing listings one by one. I designed two depths so a quick card scan stays light while full job pages bring the salary, skills and apply links that answer those questions. Every row keeps the same keys whether or not a detail was published, because I found downstream spreadsheets and agents handle a stable null far better than a shifting schema.

FAQ

Does it apply to jobs or log in?

No. It reads public Built In listings and returns links; applying stays with you.

Why are some salary fields empty?

Salary fields fill when the employer publishes a range on Built In and includeJobDetails is on. Many listings leave pay unpublished.

Can I scrape one company's jobs?

Yes. Paste the company's Built In jobs page URL into startUrls.

Responsible use

This Actor extracts public job-listing information from Built In. Use the data in line with Built In's terms, applicable laws and your own privacy and retention policies. Built In is a trademark of its owner, and this independent Actor is not affiliated with or endorsed by Built In. For questions, open a ticket in the Issues tab.