Is it legal to scrape Arc.dev?

Scraping publicly available job listings is generally considered legal for research and personal use under data scraping precedents. However, you should always review Arc's Terms of Service and ensure your activity doesn't disrupt their server operations.

Does Arc.dev have an official API?

No, Arc does not provide a public API for developers to access their job board data. Most developers use web scraping or browser automation tools to programmatically extract information from the site.

How do I avoid getting blocked by Arc?

The most effective method is using a headless browser with stealth plugins and high-quality residential proxies. You should also rotate your User-Agent and include realistic delays between requests to mimic human behavior.

What format can I export the data into?

Using tools like Automatio, you can export Arc job data into structured formats like JSON, CSV, or XML. You can also sync the results directly to Google Sheets or your own database via Webhooks.

How often should I scrape Arc to stay updated?

Since Arc updates its job board daily, a once-per-day crawl is usually sufficient for most use cases. If you are building a real-time aggregator, you might consider scraping every 4-6 hours.

Which proxies work best for Arc.dev?

Residential proxies are the most reliable choice because they are less likely to be blacklisted by Cloudflare or DataDome. Datacenter proxies are often blocked immediately due to their association with automated bots.

Can I scrape salary information from Arc?

Yes, Arc is one of the better sources for remote salary data as many listings include transparent pay ranges. This data is usually embedded within the job cards and the JSON hydration state of the page.

Does Arc use infinite scroll or pagination?

Arc typically uses a 'Load More' button or standard pagination depending on the specific search view. Your scraper must be configured to detect and interact with these elements to extract the full list of results.

How to Scrape Arc.dev: The Complete Guide to Remote Job Data

Learn how to scrape remote developer jobs, salary data, and tech stacks from Arc.dev. Extract high-quality tech listings for market research and lead...

Start Scraping Free

arc.devHard

Coverage:GlobalUnited StatesEuropeCanadaLatin AmericaAPAC

Available Data9 fields

TitlePriceLocationDescriptionImagesSeller InfoPosting DateCategoriesAttributes

All Extractable Fields

Job TitleCompany NameSalary Range (USD)Required Tech StackSecondary SkillsRemote Policy TypeTimezone Overlap RequirementFull Job DescriptionPosting DateSeniority LevelCompany Logo URLApplication LinkEmployment Type (Full-time/Contract)Company IndustryEmployee Benefits

Technical Requirements

JavaScript Required

No Login

Has Pagination

No Official API

Anti-Bot Protection Detected

CloudflareDataDomeRate LimitingBrowser FingerprintingBehavioral Analysis

About Arc

Learn what Arc offers and what valuable data can be extracted from it.

The Premier Remote Talent Marketplace

Arc (formerly CodementorX) is a leading global marketplace for vetted remote software engineers and tech professionals. Unlike generic job boards, Arc operates a highly curated platform that connects top-tier developers with companies ranging from fast-growing startups to established tech giants. The platform is particularly known for its rigorous vetting process and its focus on long-term remote roles rather than short-term gigs.

Rich Tech-Centric Data

The website is a massive repository of structured data, including detailed job descriptions, salary benchmarks across different regions, and specific technical requirements. Each listing typically contains a rich set of attributes such as required tech stacks, timezone overlap needs, and remote work policies (e.g., 'Work from Anywhere' vs. 'Specific Country').

Strategic Value of Arc Data

For recruiters and market analysts, scraping Arc.dev provides high-signal data on compensation trends and emerging technology adoption. Because the listings are vetted and updated frequently, the data is far more accurate than what is found on uncurated aggregators, making it a goldmine for competitive intelligence and specialized recruitment pipelines.

Why Scrape Arc?

Discover the business value and use cases for extracting data from Arc.

Access Vetted Talent Data

Arc filters out low-quality listings, ensuring you only extract high-value roles from verified tech companies and startups.

Real-Time Salary Benchmarking

Collect accurate remote salary and hourly rate data to create competitive compensation models for the global tech market.

Track Tech Stack Adoption

Analyze the demand for specific frameworks and programming languages like Rust, Go, or AI tools by monitoring job requirements over time.

Generate High-Quality Leads

Identify fast-growing companies that are actively scaling their engineering teams, making them prime leads for HR software or recruiting services.

Competitive Hiring Insights

Monitor which technical roles your competitors are prioritizing to gain insights into their product roadmap and expansion strategy.

Build Niche Job Portals

Aggregate premium data from Arc to populate specialized job boards focusing on specific technologies or geographic remote constraints.

Scraping Challenges

Technical challenges you may encounter when scraping Arc.

Aggressive Anti-Bot Protection

The site uses Cloudflare and DataDome, which can detect and block scrapers based on IP reputation and advanced browser fingerprints.

SPA Architecture

Being built with Next.js means content is rendered dynamically on the client side, requiring a headless browser to access the data.

Strict Rate Limiting

Frequent requests to job detail pages often trigger 429 errors or CAPTCHAs if not managed with human-like browsing patterns.

Dynamic Selectors

CSS classes are often obfuscated or change during site deployments, which can break traditional scrapers relying on static HTML attributes.

Scrape Arc with AI

No coding required. Extract data in minutes with AI-powered automation.

How It Works

Describe What You Need

Tell the AI what data you want to extract from Arc. Just type it in plain language — no coding or selectors needed.

AI Extracts the Data

Our artificial intelligence navigates Arc, handles dynamic content, and extracts exactly what you asked for.

Get Your Data

Receive clean, structured data ready to export as CSV, JSON, or send directly to your apps and workflows.

Why Use AI for Scraping

Bypass Advanced Shielding: Automatio automatically handles browser fingerprinting and uses residential proxies to bypass Cloudflare and DataDome detection effortlessly.

No-Code Visual Mapping: Extract job data by simply clicking on elements, avoiding the need to write and maintain complex XPaths or custom scripts.

Dynamic Content Execution: Automatio natively renders JavaScript and waits for elements to appear, ensuring all dynamic Next.js data is captured correctly.

Scheduled Data Extraction: Easily set your scraper to run daily to capture new job posts and changes in hiring status without any manual intervention.

Start Scraping Free

No credit card requiredFree tier availableNo setup needed

No-Code Web Scrapers for Arc

Point-and-click alternatives to AI-powered scraping

Several no-code tools like Browse.ai, Octoparse, Axiom, and ParseHub can help you scrape Arc. These tools use visual interfaces to select elements, but they come with trade-offs compared to AI-powered solutions.

Typical Workflow with No-Code Tools

Install browser extension or sign up for the platform

Navigate to the target website and open the tool

Point-and-click to select data elements you want to extract

Configure CSS selectors for each data field

Set up pagination rules to scrape multiple pages

Handle CAPTCHAs (often requires manual solving)

Configure scheduling for automated runs

Export data to CSV, JSON, or connect via API

Common Challenges

Learning curve

Understanding selectors and extraction logic takes time

Selectors break

Website changes can break your entire workflow

Dynamic content issues

JavaScript-heavy sites often require complex workarounds

CAPTCHA limitations

Most tools require manual intervention for CAPTCHAs

IP blocking

Aggressive scraping can get your IP banned

Code Examples

import requests
from bs4 import BeautifulSoup

# Note: Basic requests are often blocked by Arc's Cloudflare setup.
# Using a proper User-Agent and potentially a proxy is mandatory.
url = 'https://arc.dev/remote-jobs'
headers = {
    'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/119.0.0.0 Safari/537.36'
}

try:
    response = requests.get(url, headers=headers)
    # Check for 403 Forbidden which indicates a Cloudflare block
    if response.status_code == 200:
        soup = BeautifulSoup(response.text, 'html.parser')
        # Extract data from the Next.js JSON script for better reliability
        data_script = soup.find('script', id='__NEXT_DATA__')
        print('Successfully retrieved page source.')
    else:
        print(f'Blocked by Anti-Bot. Status code: {response.status_code}')
except Exception as e:
    print(f'Error: {e}')

When to Use

Best for static HTML pages where content is loaded server-side. The fastest and simplest approach when JavaScript rendering isn't required.

Advantages

●Fastest execution (no browser overhead)
●Lowest resource consumption
●Easy to parallelize with asyncio
●Great for APIs and static pages

Limitations

●Cannot execute JavaScript
●Fails on SPAs and dynamic content
●May struggle with complex anti-bot systems

from playwright.sync_api import sync_playwright

def scrape_arc():
    with sync_playwright() as p:
        browser = p.chromium.launch(headless=True)
        # Use a real user profile or stealth settings
        context = browser.new_context(user_agent='Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36')
        page = context.new_page()
        
        # Navigate and wait for content to hydrate
        page.goto('https://arc.dev/remote-jobs', wait_until='networkidle')
        
        # Wait for the job card elements
        page.wait_for_selector('div[class*="JobCard_container"]')
        
        jobs = page.query_selector_all('div[class*="JobCard_container"]')
        for job in jobs:
            title = job.query_selector('h2').inner_text()
            company = job.query_selector('div[class*="JobCard_company"]').inner_text()
            print(f'Scraped: {title} @ {company}')
        
        browser.close()

scrape_arc()

When to Use

Use when content loads dynamically via JavaScript, or when you need to interact with the page (clicks, scrolls, form fills). Handles modern anti-bot detection better.

Advantages

●Executes JavaScript like a real browser
●Handles SPAs and dynamic content
●Better anti-bot evasion with stealth plugins
●Can take screenshots and PDFs

Limitations

●Slower than HTTP requests
●Higher memory/CPU usage
●More complex to set up

import scrapy

class ArcSpider(scrapy.Spider):
    name = 'arc_jobs'
    start_urls = ['https://arc.dev/remote-jobs']

    def parse(self, response):
        # Scrapy needs a JS middleware (like scrapy-playwright) for Arc.dev
        for job in response.css('div[class*="JobCard_container"]'):
            yield {
                'title': job.css('h2::text').get(),
                'company': job.css('div[class*="JobCard_company"]::text').get(),
                'salary': job.css('div[class*="JobCard_salary"]::text').get(),
                'tags': job.css('div[class*="JobCard_tags"] span::text').getall()
            }

        next_page = response.css('a[class*="Pagination_next"]::attr(href)').get()
        if next_page:
            yield response.follow(next_page, self.parse)

When to Use

Ideal for large-scale crawling projects that need to scrape thousands of pages. Built-in support for rate limiting, retries, and data pipelines.

Advantages

●Built for scale (millions of pages)
●Automatic request throttling
●Built-in data export pipelines
●Middleware system for proxies/headers

Limitations

●Steeper learning curve
●Overkill for small projects
●No native JavaScript rendering

const puppeteer = require('puppeteer');

(async () => {
  const browser = await puppeteer.launch({ headless: true });
  const page = await browser.newPage();
  
  await page.setUserAgent('Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36');
  await page.goto('https://arc.dev/remote-jobs', { waitUntil: 'networkidle2' });

  const jobData = await page.evaluate(() => {
    const cards = Array.from(document.querySelectorAll('div[class*="JobCard_container"]'));
    return cards.map(card => ({
      title: card.querySelector('h2')?.innerText,
      company: card.querySelector('div[class*="JobCard_company"]')?.innerText,
      location: card.querySelector('div[class*="JobCard_location"]')?.innerText
    }));
  });

  console.log(jobData);
  await browser.close();
})();

When to Use

Choose this if you're in a Node.js/JavaScript ecosystem or need tight integration with frontend tools. Similar capabilities to Playwright.

Advantages

●Native JavaScript/TypeScript support
●Chrome DevTools Protocol access
●Large ecosystem and community
●Good for JS-heavy projects

Limitations

●Chrome-only (vs Playwright's multi-browser)
●Similar overhead to Playwright
●Less mature stealth options

How to Scrape Arc with Code

Python + Requests

import requests
from bs4 import BeautifulSoup

# Note: Basic requests are often blocked by Arc's Cloudflare setup.
# Using a proper User-Agent and potentially a proxy is mandatory.
url = 'https://arc.dev/remote-jobs'
headers = {
    'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/119.0.0.0 Safari/537.36'
}

try:
    response = requests.get(url, headers=headers)
    # Check for 403 Forbidden which indicates a Cloudflare block
    if response.status_code == 200:
        soup = BeautifulSoup(response.text, 'html.parser')
        # Extract data from the Next.js JSON script for better reliability
        data_script = soup.find('script', id='__NEXT_DATA__')
        print('Successfully retrieved page source.')
    else:
        print(f'Blocked by Anti-Bot. Status code: {response.status_code}')
except Exception as e:
    print(f'Error: {e}')

Python + Playwright

from playwright.sync_api import sync_playwright

def scrape_arc():
    with sync_playwright() as p:
        browser = p.chromium.launch(headless=True)
        # Use a real user profile or stealth settings
        context = browser.new_context(user_agent='Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36')
        page = context.new_page()
        
        # Navigate and wait for content to hydrate
        page.goto('https://arc.dev/remote-jobs', wait_until='networkidle')
        
        # Wait for the job card elements
        page.wait_for_selector('div[class*="JobCard_container"]')
        
        jobs = page.query_selector_all('div[class*="JobCard_container"]')
        for job in jobs:
            title = job.query_selector('h2').inner_text()
            company = job.query_selector('div[class*="JobCard_company"]').inner_text()
            print(f'Scraped: {title} @ {company}')
        
        browser.close()

scrape_arc()

Python + Scrapy

import scrapy

class ArcSpider(scrapy.Spider):
    name = 'arc_jobs'
    start_urls = ['https://arc.dev/remote-jobs']

    def parse(self, response):
        # Scrapy needs a JS middleware (like scrapy-playwright) for Arc.dev
        for job in response.css('div[class*="JobCard_container"]'):
            yield {
                'title': job.css('h2::text').get(),
                'company': job.css('div[class*="JobCard_company"]::text').get(),
                'salary': job.css('div[class*="JobCard_salary"]::text').get(),
                'tags': job.css('div[class*="JobCard_tags"] span::text').getall()
            }

        next_page = response.css('a[class*="Pagination_next"]::attr(href)').get()
        if next_page:
            yield response.follow(next_page, self.parse)

Node.js + Puppeteer

const puppeteer = require('puppeteer');

(async () => {
  const browser = await puppeteer.launch({ headless: true });
  const page = await browser.newPage();
  
  await page.setUserAgent('Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36');
  await page.goto('https://arc.dev/remote-jobs', { waitUntil: 'networkidle2' });

  const jobData = await page.evaluate(() => {
    const cards = Array.from(document.querySelectorAll('div[class*="JobCard_container"]'));
    return cards.map(card => ({
      title: card.querySelector('h2')?.innerText,
      company: card.querySelector('div[class*="JobCard_company"]')?.innerText,
      location: card.querySelector('div[class*="JobCard_location"]')?.innerText
    }));
  });

  console.log(jobData);
  await browser.close();
})();

What You Can Do With Arc Data

Explore practical applications and insights from Arc data.

Remote Salary Index

Human Resources departments use this to build competitive compensation packages for remote-first technical roles.

How to implement:

1Scrape all listings that include salary ranges for senior developers.
2Normalize currency to USD and calculate median pay per tech stack.
3Update the index monthly to track inflation and market demand shifts.

Use Automatio to extract data from Arc and build these applications without writing code.

More than just prompts

Supercharge your workflow with AI Automation

Automatio combines the power of AI agents, web automation, and smart integrations to help you accomplish more in less time.

AI Agents

Web Automation

Smart Workflows

Get Started Free

Pro Tips for Scraping Arc

Expert advice for successfully extracting data from Arc.

Target the __NEXT_DATA__ tag

Instead of parsing messy HTML, look for the script tag with id='__NEXT_DATA__' which contains the full JSON state of the listings.

Use Residential Proxies

To avoid being flagged by Arc's security, use residential proxies that mimic real user traffic rather than datacenter IPs.

Monitor XHR Requests

Check the browser's Network tab for internal API calls that Arc uses to load more jobs; these often provide cleaner data than the HTML.

Rotate Browser Fingerprints

Ensure your scraper alternates between different User-Agents and browser configurations to prevent behavioral detection patterns.

Implement Random Delays

Mimic human behavior by adding randomized wait times between page navigations to stay under the radar of rate-limiting systems.

Filter by Categories

Scraping specific sub-sections like '/remote-jobs/ai' is often more efficient and less likely to trigger site-wide protection than broad searches.

Testimonials

What Our Users Say

Join thousands of satisfied users who have transformed their workflow

Jonathan Kogan

Co-Founder/CEO, rpatools.io

Automatio is one of the most used for RPA Tools both internally and externally. It saves us countless hours of work and we realized this could do the same for other startups and so we choose Automatio for most of our automation needs.

Mohammed Ibrahim

CEO, qannas.pro

I have used many tools over the past 5 years, Automatio is the Jack of All trades.. !! it could be your scraping bot in the morning and then it becomes your VA by the noon and in the evening it does your automations.. its amazing!

Ben Bressington

CTO, AiChatSolutions

Automatio is fantastic and simple to use to extract data from any website. This allowed me to replace a developer and do tasks myself as they only take a few minutes to setup and forget about it. Automatio is a game changer!

Sarah Chen

Head of Growth, ScaleUp Labs

We've tried dozens of automation tools, but Automatio stands out for its flexibility and ease of use. Our team productivity increased by 40% within the first month of adoption.

David Park

Founder, DataDriven.io

The AI-powered features in Automatio are incredible. It understands context and adapts to changes in websites automatically. No more broken scrapers!

Emily Rodriguez

Marketing Director, GrowthMetrics

Automatio transformed our lead generation process. What used to take our team days now happens automatically in minutes. The ROI is incredible.

Jonathan Kogan

Co-Founder/CEO, rpatools.io

Mohammed Ibrahim

CEO, qannas.pro

Ben Bressington

CTO, AiChatSolutions

Sarah Chen

Head of Growth, ScaleUp Labs

We've tried dozens of automation tools, but Automatio stands out for its flexibility and ease of use. Our team productivity increased by 40% within the first month of adoption.

David Park

Founder, DataDriven.io

The AI-powered features in Automatio are incredible. It understands context and adapts to changes in websites automatically. No more broken scrapers!

Emily Rodriguez

Marketing Director, GrowthMetrics

Automatio transformed our lead generation process. What used to take our team days now happens automatically in minutes. The ROI is incredible.

Related Web Scraping

Frequently Asked Questions About Arc

Find answers to common questions about Arc

How to Scrape Arc.dev: The Complete Guide to Remote Job Data

About Arc

The Premier Remote Talent Marketplace

Rich Tech-Centric Data

Strategic Value of Arc Data

Why Scrape Arc?

Access Vetted Talent Data

Real-Time Salary Benchmarking

Track Tech Stack Adoption

Generate High-Quality Leads

Competitive Hiring Insights

Build Niche Job Portals

Scraping Challenges

Aggressive Anti-Bot Protection

SPA Architecture

Strict Rate Limiting

Dynamic Selectors

Scrape Arc with AI

How It Works

Why Use AI for Scraping

How to scrape with AI:

Why use AI for scraping:

No-Code Web Scrapers for Arc

Typical Workflow with No-Code Tools

Common Challenges

No-Code Web Scrapers for Arc

Typical Workflow with No-Code Tools

Common Challenges

Code Examples

How to Scrape Arc with Code

Python + Requests

Python + Playwright

Python + Scrapy

Node.js + Puppeteer

What You Can Do With Arc Data

Remote Salary Index

Recruitment Pipeline Generator

Niche Tech Aggregator Board

Tech Stack Adoption Analysis

Timezone Compatibility Tool

What You Can Do With Arc Data

Supercharge your workflow with AI Automation

Pro Tips for Scraping Arc

Target the __NEXT_DATA__ tag

Use Residential Proxies

Monitor XHR Requests

Rotate Browser Fingerprints

Implement Random Delays

Filter by Categories

What Our Users Say

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Frequently Asked Questions About Arc

Is it legal to scrape Arc.dev?

Does Arc.dev have an official API?

How do I avoid getting blocked by Arc?

What format can I export the data into?

How often should I scrape Arc to stay updated?

Which proxies work best for Arc.dev?

Can I scrape salary information from Arc?

Does Arc use infinite scroll or pagination?