Built In Jobs Scraper

Extract structured technology and startup job listings from Built In. It turns Built In search pages and company job boards into a clean dataset of titles, companies, locations, work arrangements, salary ranges, skills, dates, job descriptions, and direct application links.

Use it for hiring intelligence, recruiter sourcing, compensation research, job-alert pipelines, and AI-agent workflows that need a bounded, machine-readable Built In jobs feed. It is designed for public listings only; it does not log in, submit applications, scrape candidate profiles, or collect private account data.

What it returns

Each dataset item represents one job and uses a stable, flat shape suitable for CSV exports, databases, or Apify MCP clients.

Field	Meaning
title, companyName	Published role and hiring company
location, workplaceType, employmentType	Work location and arrangement metadata
salaryMin, salaryMax, salaryCurrency, salaryPeriod	Normalized compensation when Built In exposes it
skills	Deduplicated technologies or skills listed on the job
experienceLevel	Seniority inferred from the title where possible
description	Plain-text description preview or detail text
postedAt, validThrough	Published dates when available
jobUrl, applyUrl	Built In listing and direct employer application link

The actor preserves a consistent schema even when an optional field is unavailable: optional values are null, while skills is always an array. It also writes OUTPUT and RUN_SUMMARY to the default key-value store after every run, including valid empty results and input diagnostics.

When to use it

Use this actor when you need current Built In roles for:

• recruiters mapping companies hiring a role or technology;
• compensation analysts comparing published salary bands;
• founders monitoring competitor hiring activity;
• job-search tools that need structured roles and employer apply links; or
• an AI agent that needs a compact jobs dataset rather than a rendered results page.

Do not use it for LinkedIn, Indeed, candidate profiles, application automation, or non-Built In URLs. For a saved Built In query, provide that exact results or company-jobs URL through Start URLs. For a normal search, use the query and optional location inputs instead.

Input

searchQuery is a normal Built In role or skill search. It defaults to software engineer, which is also the quality-test-safe prefill. location is optional and accepts a full location such as Austin, TX. workplaceType selects any, remote, hybrid, or office.

Set maxResults to bound the run and its event charges. The default is 20 and the hard cap is 100. includeJobDetails defaults to true, which visits job detail pages to collect descriptions, dates, salary data, skills, and direct apply links. Set it false for a faster card-level feed. responseFormat defaults to concise, limiting descriptions to 800 characters; use detailed for up to 5,000 characters.

Search example

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

Existing Built In results page

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

Pricing and limits

The actor uses Pay per event + usage. It charges $0.00005 for the actor start and $0.003 only for each complete, validated job-scraped record persisted to the dataset. A 20-job run has a maximum event charge of $0.060 plus the platform compute and proxy usage reported separately by Apify. The actor displays the maximum event charge before it begins work and never attempts a billable write beyond maxResults.

Built In is protected by Cloudflare. The actor uses residential Apify Proxy sessions and browser rendering for the advertised mode. When the target blocks every route before any usable job is returned, the run fails honestly as UPSTREAM_FAILED and preserves diagnostics in RUN_SUMMARY; it never disguises a block as an empty search. A valid search that completes with zero matching jobs ends successfully as VALID_EMPTY.

API and MCP

Start a run through the Apify API with the same JSON input. The default dataset is the primary response surface; fetch it with the dataset URL from the run response. For agent use, prefer responseFormat: "concise" and a low maxResults so each item remains easy to reason over.

curl -X POST "https://api.apify.com/v2/acts/khadinakbar~built-in-jobs-scraper/runs" \
  -H "Authorization: Bearer $APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"searchQuery":"data engineer","workplaceType":"remote","maxResults":10}'

Notes and compliance

Built In content, layout, availability, and bot controls can change. Use reasonable result caps and schedule monitoring runs conservatively. You are responsible for ensuring your use of exported data complies with applicable laws, the source website’s terms, and your internal privacy and retention policies. This actor extracts public job-listing information and does not bypass logins or collect account-only data.

For repeat monitoring, keep each saved task focused on a real hiring question—such as remote machine-learning roles or a specific company’s open jobs—and use the same bounded result cap. That makes changes between runs easy to compare and keeps both cost and downstream automation predictable.