Scrape Glassdoor job listings

Pull job titles, companies, locations, and salary estimates from Glassdoor search results.

Prerequisites

• A Browserless API token from your account dashboard

Steps

The examples below navigate to a pre-formed Glassdoor search URL and extract job listing data.

Selector stability

Glassdoor frequently updates its markup. If the selectors below stop returning results, inspect the page with browser DevTools and update the CSS selectors to match the current DOM structure.

AI Agent

Use the Browserless MCP server to scrape job listings from Glassdoor from any MCP-compatible AI agent (Claude Desktop, Cursor, Windsurf, ChatGPT, etc.).

1. Connect the MCP server

Send this prompt to your AI agent to install the Browserless MCP server:

Go to https://github.com/browserless/browserless-mcp/blob/main/install.md
and follow the instructions to install the Browserless MCP server
for my client.

2. Scrape Glassdoor

Use browserless_smartscraper. Glassdoor has aggressive bot detection and smartscraper handles it automatically.

Use the browserless_smartscraper tool to scrape job listings
from https://www.glassdoor.com/Job/new-york-jobs-SRCH_IL.0,8_IC1132348.htm
and return the results as markdown

REST API

Send the BQL mutation over HTTP to the stealth endpoint. No browser library or BQL IDE required.

cURL

1. Send the request

curl -X POST \
  "https://production-sfo.browserless.io/stealth/bql?token=YOUR_API_TOKEN_HERE&proxy=residential&proxyCountry=us" \
  -H "Content-Type: application/json" \
  -d '{
    "query": "mutation ScrapeGlassdoor { goto(url: \"https://www.glassdoor.com/Job/new-york-software-engineer-jobs-SRCH_IL.0,8_IC1132348_KO9,26.htm\", waitUntil: networkIdle) { status } jobs: mapSelector(selector: \"[data-test='\''jobListing'\'']\") { title: mapSelector(selector: \"a[data-test='\''job-title'\'']\") { innerText } company: mapSelector(selector: \"[data-test='\''employer-name'\'']\") { innerText } location: mapSelector(selector: \"[data-test='\''emp-location'\'']\") { innerText } salary: mapSelector(selector: \"[data-test='\''detailSalary'\'']\") { innerText } } }",
    "variables": {},
    "operationName": "ScrapeGlassdoor"
  }'

2. Check the output

{
  "data": {
    "goto": { "status": 200 },
    "jobs": [
      {
        "title": [{ "innerText": "Software Engineer" }],
        "company": [{ "innerText": "TechCorp" }],
        "location": [{ "innerText": "New York, NY" }],
        "salary": [{ "innerText": "$120K – $180K (Glassdoor est.)" }]
      },
      {
        "title": [{ "innerText": "Senior Software Engineer" }],
        "company": [{ "innerText": "BuildCo" }],
        "location": [{ "innerText": "New York, NY (Remote)" }],
        "salary": [{ "innerText": "$150K – $220K (Glassdoor est.)" }]
      }
    ]
  }
}

JavaScript

1. Send the request

const query = `mutation ScrapeGlassdoor {
  goto(
    url: "https://www.glassdoor.com/Job/new-york-software-engineer-jobs-SRCH_IL.0,8_IC1132348_KO9,26.htm"
    waitUntil: networkIdle
  ) {
    status
  }
  jobs: mapSelector(selector: "[data-test='jobListing']") {
    title: mapSelector(selector: "a[data-test='job-title']") {
      innerText
    }
    company: mapSelector(selector: "[data-test='employer-name']") {
      innerText
    }
    location: mapSelector(selector: "[data-test='emp-location']") {
      innerText
    }
    salary: mapSelector(selector: "[data-test='detailSalary']") {
      innerText
    }
  }
}`;

const response = await fetch(
  'https://production-sfo.browserless.io/stealth/bql?token=YOUR_API_TOKEN_HERE&proxy=residential&proxyCountry=us',
  {
    method: 'POST',
    headers: { 'Content-Type': 'application/json' },
    body: JSON.stringify({ query, variables: {}, operationName: 'ScrapeGlassdoor' }),
  }
);

const { data } = await response.json();
const jobs = data.jobs.map((job) => ({
  title: job.title?.[0]?.innerText ?? '',
  company: job.company?.[0]?.innerText ?? '',
  location: job.location?.[0]?.innerText ?? '',
  salary: job.salary?.[0]?.innerText ?? '',
}));
console.log(JSON.stringify(jobs, null, 2));

2. Check the output

{
  "data": {
    "goto": { "status": 200 },
    "jobs": [
      {
        "title": [{ "innerText": "Software Engineer" }],
        "company": [{ "innerText": "TechCorp" }],
        "location": [{ "innerText": "New York, NY" }],
        "salary": [{ "innerText": "$120K – $180K (Glassdoor est.)" }]
      },
      {
        "title": [{ "innerText": "Senior Software Engineer" }],
        "company": [{ "innerText": "BuildCo" }],
        "location": [{ "innerText": "New York, NY (Remote)" }],
        "salary": [{ "innerText": "$150K – $220K (Glassdoor est.)" }]
      }
    ]
  }
}

Python

1. Install dependencies

pip install requests

2. Send the request

import requests

query = """
mutation ScrapeGlassdoor {
  goto(
    url: "https://www.glassdoor.com/Job/new-york-software-engineer-jobs-SRCH_IL.0,8_IC1132348_KO9,26.htm"
    waitUntil: networkIdle
  ) {
    status
  }
  jobs: mapSelector(selector: "[data-test='jobListing']") {
    title: mapSelector(selector: "a[data-test='job-title']") {
      innerText
    }
    company: mapSelector(selector: "[data-test='employer-name']") {
      innerText
    }
    location: mapSelector(selector: "[data-test='emp-location']") {
      innerText
    }
    salary: mapSelector(selector: "[data-test='detailSalary']") {
      innerText
    }
  }
}
"""

response = requests.post(
    'https://production-sfo.browserless.io/stealth/bql',
    params={
        'token': 'YOUR_API_TOKEN_HERE',
        'proxy': 'residential',
        'proxyCountry': 'us',
    },
    json={'query': query, 'variables': {}, 'operationName': 'ScrapeGlassdoor'},
)

data = response.json()['data']
for job in data['jobs']:
    title = job['title'][0]['innerText'] if job['title'] else ''
    company = job['company'][0]['innerText'] if job['company'] else ''
    location = job['location'][0]['innerText'] if job['location'] else ''
    salary = job['salary'][0]['innerText'] if job['salary'] else ''
    print(f'{title} at {company} — {location} — {salary}')

3. Check the output

{
  "data": {
    "goto": { "status": 200 },
    "jobs": [
      {
        "title": [{ "innerText": "Software Engineer" }],
        "company": [{ "innerText": "TechCorp" }],
        "location": [{ "innerText": "New York, NY" }],
        "salary": [{ "innerText": "$120K – $180K (Glassdoor est.)" }]
      },
      {
        "title": [{ "innerText": "Senior Software Engineer" }],
        "company": [{ "innerText": "BuildCo" }],
        "location": [{ "innerText": "New York, NY (Remote)" }],
        "salary": [{ "innerText": "$150K – $220K (Glassdoor est.)" }]
      }
    ]
  }
}

Java

1. Send the request

import java.net.URI;
import java.net.http.*;

String token = "YOUR_API_TOKEN_HERE";
String endpoint = "https://production-sfo.browserless.io/stealth/bql?token="
    + token + "&proxy=residential&proxyCountry=us";

String query = """
    mutation ScrapeGlassdoor {
      goto(url: "https://www.glassdoor.com/Job/new-york-software-engineer-jobs-SRCH_IL.0,8_IC1132348_KO9,26.htm", waitUntil: networkIdle) { status }
      jobs: mapSelector(selector: "[data-test='jobListing']") {
        title: mapSelector(selector: "a[data-test='job-title']") { innerText }
        company: mapSelector(selector: "[data-test='employer-name']") { innerText }
        location: mapSelector(selector: "[data-test='emp-location']") { innerText }
        salary: mapSelector(selector: "[data-test='detailSalary']") { innerText }
      }
    }
    """;

String payload = "{\"query\": " + com.google.gson.JsonParser.parseString(query) + ", \"variables\": {}, \"operationName\": \"ScrapeGlassdoor\"}";

HttpClient client = HttpClient.newHttpClient();
HttpRequest request = HttpRequest.newBuilder()
    .uri(URI.create(endpoint))
    .header("Content-Type", "application/json")
    .POST(HttpRequest.BodyPublishers.ofString(payload))
    .build();

HttpResponse<String> response = client.send(request, HttpResponse.BodyHandlers.ofString());
System.out.println(response.body());

2. Check the output

{
  "data": {
    "goto": { "status": 200 },
    "jobs": [
      {
        "title": [{ "innerText": "Software Engineer" }],
        "company": [{ "innerText": "TechCorp" }],
        "location": [{ "innerText": "New York, NY" }],
        "salary": [{ "innerText": "$120K – $180K (Glassdoor est.)" }]
      },
      {
        "title": [{ "innerText": "Senior Software Engineer" }],
        "company": [{ "innerText": "BuildCo" }],
        "location": [{ "innerText": "New York, NY (Remote)" }],
        "salary": [{ "innerText": "$150K – $220K (Glassdoor est.)" }]
      }
    ]
  }
}

C#

1. Send the request

using System.Net.Http;
using System.Text;
using System.Text.Json;

string token = "YOUR_API_TOKEN_HERE";
string endpoint = $"https://production-sfo.browserless.io/stealth/bql?token={token}&proxy=residential&proxyCountry=us";

var payload = new
{
    query = @"mutation ScrapeGlassdoor {
      goto(url: ""https://www.glassdoor.com/Job/new-york-software-engineer-jobs-SRCH_IL.0,8_IC1132348_KO9,26.htm"", waitUntil: networkIdle) { status }
      jobs: mapSelector(selector: ""[data-test='jobListing']"") {
        title: mapSelector(selector: ""a[data-test='job-title']"") { innerText }
        company: mapSelector(selector: ""[data-test='employer-name']"") { innerText }
        location: mapSelector(selector: ""[data-test='emp-location']"") { innerText }
        salary: mapSelector(selector: ""[data-test='detailSalary']"") { innerText }
      }
    }",
    variables = new { },
    operationName = "ScrapeGlassdoor",
};

using (HttpClient httpClient = new HttpClient())
{
    var content = new StringContent(
        JsonSerializer.Serialize(payload), Encoding.UTF8, "application/json");
    var response = await httpClient.PostAsync(endpoint, content);
    string body = await response.Content.ReadAsStringAsync();
    Console.WriteLine(body);
}

2. Check the output

{
  "data": {
    "goto": { "status": 200 },
    "jobs": [
      {
        "title": [{ "innerText": "Software Engineer" }],
        "company": [{ "innerText": "TechCorp" }],
        "location": [{ "innerText": "New York, NY" }],
        "salary": [{ "innerText": "$120K – $180K (Glassdoor est.)" }]
      },
      {
        "title": [{ "innerText": "Senior Software Engineer" }],
        "company": [{ "innerText": "BuildCo" }],
        "location": [{ "innerText": "New York, NY (Remote)" }],
        "salary": [{ "innerText": "$150K – $220K (Glassdoor est.)" }]
      }
    ]
  }
}

Frameworks

Connect through stealth mode and a residential proxy so Glassdoor sees traffic that looks like it's coming from a real US-based browser, then extract job listing data from the fully rendered page.

Puppeteer

View Full Code on GitHub

1. Install dependencies

npm install puppeteer-core

2. Connect and scrape

import puppeteer from 'puppeteer-core';

const browser = await puppeteer.connect({
  browserWSEndpoint:
    'wss://production-sfo.browserless.io/stealth?token=YOUR_API_TOKEN_HERE&proxy=residential&proxyCountry=us',
});

try {
  const page = await browser.newPage();
  await page.goto(
    'https://www.glassdoor.com/Job/new-york-software-engineer-jobs-SRCH_IL.0,8_IC1132348_KO9,26.htm',
    { waitUntil: 'networkidle2' }
  );

  const jobs = await page.evaluate(() =>
    Array.from(document.querySelectorAll('[data-test="jobListing"]')).map((card) => ({
      title: card.querySelector('a[data-test="job-title"]')?.innerText?.trim() ?? '',
      company: card.querySelector('[data-test="employer-name"]')?.innerText?.trim() ?? '',
      location: card.querySelector('[data-test="emp-location"]')?.innerText?.trim() ?? '',
      salary: card.querySelector('[data-test="detailSalary"]')?.innerText?.trim() ?? '',
    }))
  );

  console.log(JSON.stringify(jobs, null, 2));
} finally {
  await browser.close();
}

3. Check the output

Run with node scrape-glassdoor.mjs. You get one object per job card, each with title, company, location, and salary already grouped. No index-stitching required because we're selecting within each card element.

Playwright

View Full Code on GitHub

1. Install dependencies

npm install playwright-core

2. Connect and scrape

import { chromium } from 'playwright-core';

const browser = await chromium.connectOverCDP(
  'wss://production-sfo.browserless.io?token=YOUR_API_TOKEN_HERE&stealth&proxy=residential&proxyCountry=us'
);

try {
  const context = browser.contexts()[0];
  const page = await context.newPage();
  await page.goto(
    'https://www.glassdoor.com/Job/new-york-software-engineer-jobs-SRCH_IL.0,8_IC1132348_KO9,26.htm',
    { waitUntil: 'networkidle' }
  );

  const jobs = await page.evaluate(() =>
    Array.from(document.querySelectorAll('[data-test="jobListing"]')).map((card) => ({
      title: card.querySelector('a[data-test="job-title"]')?.innerText?.trim() ?? '',
      company: card.querySelector('[data-test="employer-name"]')?.innerText?.trim() ?? '',
      location: card.querySelector('[data-test="emp-location"]')?.innerText?.trim() ?? '',
      salary: card.querySelector('[data-test="detailSalary"]')?.innerText?.trim() ?? '',
    }))
  );

  console.log(JSON.stringify(jobs, null, 2));
} finally {
  await browser.close();
}

3. Check the output

Run with node scrape-glassdoor.mjs. You get one object per job card, each with title, company, location, and salary already grouped. No index-stitching required because we're selecting within each card element.

BQL

View Full Code on GitHub

1. Write the mutation

Navigate directly to the Glassdoor search results URL and use mapSelector to pull structured data from each job card. We send this to the /stealth/bql endpoint (not the default /bql) because Glassdoor's bot detection will block a plain browser session before the page even loads.

mutation ScrapeGlassdoor {
  goto(
    url: "https://www.glassdoor.com/Job/new-york-software-engineer-jobs-SRCH_IL.0,8_IC1132348_KO9,26.htm"
    waitUntil: networkIdle
  ) {
    status
  }

  jobs: mapSelector(selector: "[data-test='jobListing']") {
    title: mapSelector(selector: "a[data-test='job-title']") {
      innerText
    }
    company: mapSelector(selector: "[data-test='employer-name']") {
      innerText
    }
    location: mapSelector(selector: "[data-test='emp-location']") {
      innerText
    }
    salary: mapSelector(selector: "[data-test='detailSalary']") {
      innerText
    }
  }
}

2. Run it

Paste into the BQL IDE and click Run.

3. Check the output

Each entry under jobs is already structured by card. mapSelector nests its results relative to each matched parent element, so you don't need to stitch fields together by index.

{
  "data": {
    "goto": { "status": 200 },
    "jobs": [
      {
        "title": [{ "innerText": "Software Engineer" }],
        "company": [{ "innerText": "TechCorp" }],
        "location": [{ "innerText": "New York, NY" }],
        "salary": [{ "innerText": "$120K – $180K (Glassdoor est.)" }]
      },
      {
        "title": [{ "innerText": "Senior Software Engineer" }],
        "company": [{ "innerText": "BuildCo" }],
        "location": [{ "innerText": "New York, NY (Remote)" }],
        "salary": [{ "innerText": "$150K – $220K (Glassdoor est.)" }]
      }
    ]
  }
}

Next steps

Scrape Etsy Product Listings

extract product data from another bot-protected marketplace

Solving Cloudflare Challenges

bypass Cloudflare protection on other targets

Change Your Browser's IP Address Using Proxies

control which IP address target sites see