BuiltIn Jobs Scraper

BuiltIn Jobs Scraper — Tech Job Listings from BuiltIn.com

Scrape BuiltIn.com tech job listings at scale. Extract job titles, companies, salaries, seniority levels, workplace types, industry categories, skills, and description snippets. Search by keyword, location, or any custom BuiltIn.com URL. Export as JSON, CSV, or Excel.

Extract structured tech job data from BuiltIn.com — search by keyword, location, or custom URL and get salaries, seniority levels, workplace types, categories, top skills, and descriptions ready for analysis, monitoring, or integration.

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Apify Actor: parsebird/builtin-jobs-scraper — scrapes BuiltIn.com tech job listings. $0.99/1000 results. Call via ApifyClient: client.actor("parsebird/builtin-jobs-scraper").call(run_input={"keyword": "software engineer", "results_wanted": 20}). Inputs: keyword (string, default "software engineer"), location (string, optional city filter), startUrl (string, optional — overrides keyword/location with a custom BuiltIn.com URL), results_wanted (integer, default 20), max_pages (integer, default 20). Output: dataset with title, company, category, location, date_posted, description_text, url, source, workplace_type, salary_range_short, seniority, skills, company_url, scrapedAt. API docs: https://docs.apify.com/api/v2 Token: https://console.apify.com/settings/integrations

What is BuiltIn Jobs Scraper?

BuiltIn Jobs Scraper is an Apify Actor that extracts tech job listings from BuiltIn.com — the leading US platform for tech and startup careers, featuring job postings from thousands of companies across all major tech hubs. It scrapes structured data from job listing pages including titles, companies, salaries, seniority levels, workplace types, industry categories, top skills, and description snippets.

Think of it as a BuiltIn.com API alternative — no official public API exists, but this scraper delivers the same structured job data at scale. It's built for recruitment analytics, salary benchmarking, tech hiring research, lead generation, and job market monitoring.

What data can you extract from BuiltIn.com?

Field	Description
title	Job title (e.g., "Senior Software Engineer", "Data Scientist")
company	Employer name
category	Industry categories (e.g., ["Software", "Fintech", "Machine Learning"])
location	Job location (e.g., "San Francisco, CA, USA")
date_posted	Relative posting time (e.g., "6 Hours Ago", "Reposted 4 Hours Ago")
description_text	Job description snippet from the listing card
description_html	Full job description in HTML (when available)
url	Direct link to the job posting on BuiltIn.com
source	Data source — always "builtin.com"
company_overview	Company description (when available)
workplace_type	Remote, Hybrid, In-Office, or combinations
salary_range_short	Salary range (e.g., "$150K-$200K Annually")
seniority	Experience level (Entry level, Junior, Mid level, Senior level)
skills	Top skills listed on the job card (e.g., ["Python", "AWS", "React"])
company_url	Link to the company profile on BuiltIn.com
scrapedAt	ISO timestamp of extraction

How to scrape BuiltIn.com

1. Go to BuiltIn Jobs Scraper on Apify Store and click Try for free
2. Enter a search keyword — Use the default "software engineer" or type any role (e.g., "Data Scientist", "Product Manager", "Machine Learning Engineer")
3. Set a location (optional) — Filter by city (e.g., "San Francisco", "New York", "Austin") or leave empty for all locations
4. Or paste a custom URL — Use startUrl to paste any BuiltIn.com search URL with pre-applied filters (overrides keyword and location)
5. Set the result limit — Start with 20 for a quick test, increase to 100–500 for larger datasets
6. Configure proxy (optional) — No proxy by default; enable residential proxies for large-scale or frequent scraping
7. Run the scraper — Click Start and wait for results
8. Export your data — Download as JSON, CSV, or Excel, or access via the Apify API

Input parameters

Parameter	Type	Required	Default	Description
keyword	string	No	"software engineer"	Job search keyword (e.g., "Data Scientist", "Product Manager")
location	string	No	—	City or location filter (e.g., "San Francisco", "New York")
startUrl	string	No	—	Custom BuiltIn.com search URL (overrides keyword and location)
results_wanted	integer	No	20	Maximum number of jobs to collect
max_pages	integer	No	20	Maximum listing pages to visit (up to 25 jobs per page)
proxyConfiguration	object	No	No proxy	Proxy settings for the run

Output example

{
  "title": "Senior Software Engineer",
  "company": "TechCorp Inc",
  "category": ["Software", "Artificial Intelligence", "Machine Learning"],
  "location": "San Francisco, CA, USA",
  "date_posted": "6 Hours Ago",
  "description_html": null,
  "description_text": "We are seeking an experienced Senior Software Engineer to join our AI team. You will design and build scalable backend systems...",
  "url": "https://builtin.com/job/senior-software-engineer/12345",
  "source": "builtin.com",
  "company_overview": null,
  "workplace_type": "Remote",
  "salary_range_short": "$150K-$200K Annually",
  "seniority": "Senior level",
  "skills": ["Python", "AWS", "Kafka", "React"],
  "company_url": "https://builtin.com/company/techcorp-inc",
  "listingPage": 1,
  "listingUrl": "https://builtin.com/jobs?search=software+engineer",
  "scrapedAt": "2026-06-09T12:00:00.000Z"
}

Download results in JSON, CSV, Excel, or access via the Apify API.

Use cases

• 📊 Recruitment intelligence — Build hiring datasets by role, company, and location across the US tech market
• 💰 Salary benchmarking — Compare salary ranges for tech roles across cities like San Francisco, New York, Austin, and Seattle
• 🎯 Sales prospecting — Discover companies actively hiring for specific roles and build targeted outreach lists
• 📈 Tech hiring research — Analyze skills demand, seniority distribution, and workplace type trends (remote vs. hybrid vs. in-office)
• 🏢 Competitive intelligence — Monitor competitor hiring patterns and expansion plans based on job postings
• 🤖 Training data collection — Build datasets of tech job listings for NLP, resume matching, or recommendation systems
• 📅 Job market monitoring — Schedule regular runs with Apify Schedules to track new postings
• 🔌 Pipeline integration — Feed job data into Google Sheets, Slack, Zapier, Make, or custom systems via Apify Integrations

Tips for best results

Choose relevant keywords

• Use specific job titles for targeted results (e.g., "Machine Learning Engineer" rather than "engineer")
• Try variations — "ML Engineer", "Machine Learning Engineer", and "AI Engineer" may return different results
• Combine keywords for niche roles (e.g., "Senior React Developer")

Optimize collection size

• Start with 20–50 results for testing
• Increase to 100–500 for production datasets
• Use max_pages to control scraping depth — each page has up to 25 jobs

Use proxy configuration

For reliable, large-scale scraping, residential proxies are recommended:

{
    "proxyConfiguration": {
        "useApifyProxy": true,
        "apifyProxyGroups": ["RESIDENTIAL"]
    }
}

Monitor data quality

• Check that job descriptions are complete
• Verify salary data is extracted when available — not all employers list salaries
• Review company information for completeness

How to use via API — Python

from apify_client import ApifyClient

client = ApifyClient("YOUR_API_TOKEN")

run = client.actor("parsebird/builtin-jobs-scraper").call(run_input={
    "keyword": "data scientist",
    "location": "San Francisco",
    "results_wanted": 100,
    "max_pages": 10,
})

for job in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(f"{job['title']} at {job['company']} — {job['location']} — {job.get('salary_range_short', 'N/A')}")

How to use via API — JavaScript

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_API_TOKEN' });

const run = await client.actor('parsebird/builtin-jobs-scraper').call({
    keyword: 'data scientist',
    location: 'San Francisco',
    results_wanted: 100,
    max_pages: 10,
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach(job => {
    console.log(`${job.title} at ${job.company} — ${job.location} — ${job.salary_range_short || 'N/A'}`);
});

How much does it cost to scrape BuiltIn.com?

BuiltIn Jobs Scraper uses pay-per-event pricing — you pay a fixed price per result. Platform usage (compute, proxy) is not charged separately.

How much does it cost to scrape 1,000 BuiltIn.com jobs?

$0.99. Each job listing costs $0.00099. New users get a free trial with $5 of platform credit — enough for approximately 5,000 job listings.

How much does it cost to scrape 100 BuiltIn.com jobs?

$0.099. A quick export covering one keyword or location search.

Pricing

Event	Price per event	Price per 1,000
Result	$0.00099	$0.99

Each job listing pushed to the dataset counts as one result.

Typical costs:

• 20 jobs (quick test): ~$0.02
• 100 jobs (one search): ~$0.10
• 500 jobs (multi-page run): ~$0.50
• 1,000 jobs (large dataset): ~$0.99

Is it legal to scrape BuiltIn.com?

This Actor extracts publicly available data from BuiltIn.com — the same job listing data any browser user can see on the search results pages. No login or authentication is used. The scraper accesses only publicly visible job postings.

Web scraping of publicly available data is generally legal in the United States and the European Union, as established by the hiQ Labs v. LinkedIn ruling. For more information, see Apify's guide on the legality of web scraping.

Users are responsible for ensuring their use of extracted data complies with applicable laws and BuiltIn.com's Terms of Service in their jurisdiction.

Related Actors

Looking for more job scraping and data extraction tools? Check out these ParseBird actors:

• Bayt Jobs Scraper — Scrape job listings from Bayt.com across the Middle East and 30+ countries
• RozeePk Jobs Scraper — Scrape job listings from Rozee.pk, Pakistan's largest job portal
• Hiring.cafe Scraper — Scrape job listings from Hiring.cafe with 20+ filters
• Yandex Maps Scraper — Extract business data and reviews from Yandex Maps

Browse all ParseBird actors on Apify Store.

FAQ

What search inputs does the scraper support? Three modes: (1) keyword search — enter any job title or keyword, (2) keyword + location — combine with a city name, (3) custom URL — paste any BuiltIn.com search URL with pre-applied filters for maximum flexibility.

Can I search for jobs in specific cities? Yes. Set the location field to any city name (e.g., "San Francisco", "New York", "Austin", "Seattle", "Chicago"). Alternatively, use startUrl with a BuiltIn.com URL that already has location filters applied.

Why are some fields empty or null? Some fields like salary, seniority, or workplace type depend on what the employer includes in the job posting. Empty values mean the source listing did not provide that information. company_overview and description_html are only available from individual job detail pages and may be null when scraping listing pages.

How many jobs can I collect per run? Up to 1,000 jobs per run. Each listing page contains up to 25 jobs. Set results_wanted and max_pages to control how many jobs you collect. For very large datasets, run the scraper multiple times with different keywords or locations.

Can I schedule recurring runs? Yes. Use Apify Schedules to run daily, weekly, or at any interval. Monitor new tech job postings by comparing datasets between runs.

Can I access the data via API? Yes. Use the Apify API or the official Python and JavaScript client libraries to run the scraper and retrieve results programmatically.

What export formats are supported? JSON, CSV, Excel (XLSX), XML, HTML, and RSS. Download directly from the Apify Console or via the API.

Is there a free trial? Yes. New Apify users get $5 of free platform credit, which covers approximately 5,000 BuiltIn.com job listings.

Do I need proxies? For small runs (under 100 jobs), proxies are optional. For large-scale or frequent scraping, residential proxies are recommended for reliability. Proxies are disabled by default — enable them in the Advanced settings.

I found an issue or have a feature request. Open an issue on the Issues tab or contact ParseBird via the Apify Console.