Built In Tech Jobs Scraper

Scrape tech and startup jobs from Built In (builtin.com) at scale — across the national board and every major US tech hub: New York, San Francisco, Austin, Chicago, Boston, Los Angeles, Seattle, Colorado, Washington DC, Atlanta, Dallas and Miami.

The Actor crawls every region, de-duplicates, and returns tens of thousands of unique job listings in a single run.

✨ What you get

• Full coverage: national board + 13 regional tech hubs, de-duplicated
• Rich data per job: title, company, salary, skills, experience level, remote policy, location, industries, posting date
• Flexible filters: keyword, remote policy, experience level, company size, category, days-since-updated
• Built for scheduling — run it daily for a continuously fresh US tech-jobs feed

📦 Output fields

jobId, title, url, company, companyUrl, companyLogoUrl, remoteType, location, experienceLevel, salary, industries, skills, description, postedLabel, scrapedAt

🚀 Example input

{
  "categories": ["dev-engineering"],
  "remote": ["remote"],
  "maxJobs": 5000
}

💡 Use cases

• Recruitment & sourcing — a fresh, deduplicated feed of US tech & startup roles
• Job boards & aggregators — power a tech-jobs section with always-current listings
• Labor market research — track hiring trends, salaries and in-demand skills by city
• Sales & lead gen — find companies actively hiring tech talent

Schedule it on Apify to run daily for a continuously updated tech-jobs dataset.

Who is it for?

• Recruiters and sourcers building a fresh, deduplicated feed of US tech and startup roles.
• Talent-market analysts tracking hiring volume by city, seniority and remote policy.
• Compensation teams benchmarking advertised salary bands by role and region.
• Job boards and aggregators seeding a US tech listings catalogue.
• Founders and investors reading hiring as a growth signal across a portfolio.
• Career platforms powering search and alerting for engineering candidates.

Input parameters

Parameter	Type	Default	Description
regions	array	all 13 hubs + national	Which Built In boards to crawl
searchTitle	string	(empty)	Keyword matched against the job title
remote	array	(none)	Remote policy filter
experience	array	(none)	Seniority filter
companySizes	array	(none)	Company size filter
categories	array	(none)	Job category, e.g. dev-engineering
daysSinceUpdated	integer	(none)	Only postings refreshed within N days
maxJobs	integer	500	Stop after this many unique jobs; 0 means no limit
proxyConfiguration	object	Apify Proxy	Proxy settings

Tips for best results

• Leave regions alone for full coverage. The national board and the hub boards overlap heavily, and the Actor deduplicates across them, so crawling all of them is how you get the complete picture rather than thirteen copies of it.
• salary is the advertised band, not an offer. Built In publishes it on roughly nine listings in ten, written as 216K-276K Annually; salaryMin and salaryMax give the same band as plain numbers you can average, and salaryPeriod tells you whether it is annual or hourly. Treat an absent band as "not disclosed" rather than zero.
• Filter with categories before searchTitle. The category filter is applied by the board itself, so it cuts the crawl down instead of downloading everything and discarding most of it.
• jobId is the deduplication key across scheduled runs; the URL slug changes when a posting is edited.
• Schedule it daily if you want a moving picture — postings turn over quickly and postedLabel only tells you how the board described the age at collection time.
• Set maxJobs to 0 for the full export. The run then walks every region until each runs dry, and stops itself just before the run's own timeout with everything found so far — so a long export is safe to leave running.

Integrations

Connect the dataset to Make, Zapier, Airbyte, Google Sheets, Slack, Greenhouse, Lever or any HTTP endpoint through Apify integrations, or schedule a run and push results into an ATS or warehouse with a webhook.

API usage

from apify_client import ApifyClient

client = ApifyClient("<YOUR_API_TOKEN>")
run = client.actor("logiover/built-in-tech-jobs-scraper").call(run_input={
    "categories": ["dev-engineering"],
    "remote": ["remote"],
    "maxJobs": 5000,
})
rows = list(client.dataset(run["defaultDatasetId"]).iterate_items())
paid = [r for r in rows if r["salary"]]
print(f"{len(paid)} of {len(rows)} postings disclose a salary band")

Use with AI agents (MCP)

The Actor is callable from the Apify MCP server, so an assistant can pull live US tech job listings directly and answer questions about roles, companies and hiring trends.

FAQ

Do I need a Built In account or API key?

No. This Actor reads the public job boards; there is nothing to register and nothing to rotate.

How many jobs can one run return?

Tens of thousands. The Actor crawls the national board plus thirteen regional hubs and deduplicates across all of them, so the ceiling is the size of the board rather than a per-run cap. maxJobs is prefilled at 500 so a first run finishes in about a minute; set it to 0 for the full export and raise the run timeout to match.

What happens if the run hits its time limit?

It stops itself a little before the limit and finishes normally, keeping every job already collected, and says so in the log. Nothing is lost and the run is not recorded as timed out — you can pick up from there with a narrower region list or a longer timeout.

Why do some jobs have no salary?

Because the employer did not publish one — about one listing in ten. US pay-transparency laws vary by state, so disclosure is common in New York and Colorado and patchy elsewhere. The field is left empty rather than guessed, and the numeric bounds are left empty with it.

Are remote jobs included?

Yes — remote is one of the regions crawled by default, and every row carries a remoteType so you can filter after the fact.

Does it collect recruiter contact details?

No. The Actor collects the public posting: title, company, location, salary, skills and description, with a url to the listing itself.

Can I export to CSV or Excel?

Yes — every run's dataset exports to JSON, CSV, Excel, XML or JSONL.

How fresh is the data?

Each run reads the boards live, so listings are as current as Built In itself at the moment you run it.

Why did my run return fewer jobs than expected?

Usually filters that combine to a narrow set — a category plus a seniority plus a remote policy can cut a board to very little. Clear them one at a time to see which one bites.

Is it legal to scrape Built In?

Built In publishes its job boards openly so that candidates can find roles, and this Actor reads only those public listing pages — no accounts, no logins. Job postings are commercial advertisements placed by employers. As with any scraping, you remain responsible for how you use the data, including under applicable data-protection law, and for respecting the site's terms in your own jurisdiction.

Related scrapers

• Greenhouse Job Board Scraper — postings straight from employer ATS boards.
• Lever Postings Scraper — the same for Lever-hosted boards.
• Himalayas Remote Jobs Scraper — remote-first roles worldwide.
• Welcome to the Jungle Jobs Scraper — European tech and startup roles.