JOB MARKET & HR

Job Scraping & Listing Aggregation

Job scraping at scale: pull job postings from any board or careers page to build job boards, analyze hiring trends, and research compensation.

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Job listings from many boards merging into one feed

Job Data Is Scattered

Job listings are spread across hundreds of job boards, company career pages, and staffing sites. Building a comprehensive view of the job market requires aggregating from all these sources.

Each platform has different formats and structures. Manual collection doesn't scale, and APIs are often limited or expensive.

WebScraping.AI Solution

  • Any Source: Extract jobs from any job board or careers page
  • Structured Data: Get uniform job data regardless of source format
  • Rich Details: Capture salary, requirements, benefits, and more
  • AI-Powered: Intelligent extraction handles varying page layouts

Job Data Extraction

Capture complete job listing details

Job Details

Title, description, requirements, and responsibilities.

Compensation

Salary ranges, benefits, and equity information.

Company Info

Employer name, size, industry, and location.

Requirements

Skills, experience level, and qualifications.

Code Examples

Extract job listing data from any source

curl -G "https://api.webscraping.ai/ai/fields" \
  --data-urlencode "api_key=YOUR_API_KEY" \
  --data-urlencode "url=https://company.com/careers/senior-engineer" \
  --data-urlencode "fields[job_title]=Job title" \
  --data-urlencode "fields[company]=Company name" \
  --data-urlencode "fields[location]=Job location" \
  --data-urlencode "fields[remote]=Is remote work available (yes/no/hybrid)" \
  --data-urlencode "fields[salary_min]=Minimum salary if listed" \
  --data-urlencode "fields[salary_max]=Maximum salary if listed" \
  --data-urlencode "fields[experience_level]=Required experience level" \
  --data-urlencode "fields[employment_type]=Full-time, part-time, contract, etc." \
  --data-urlencode "fields[required_skills]=Required skills, comma-separated" \
  --data-urlencode "fields[benefits]=Benefits mentioned, comma-separated" \
  --data-urlencode "fields[description]=Job description summary" \
  --data-urlencode "fields[posted_date]=When the job was posted"
# Response:
# {
#   "result": {
#     "job_title": "Senior Software Engineer",
#     "company": "TechCorp",
#     "location": "San Francisco, CA",
#     "remote": "hybrid",
#     "salary_min": "150000",
#     "salary_max": "200000",
#     "experience_level": "5+ years",
#     "employment_type": "Full-time",
#     "required_skills": "Python, AWS, PostgreSQL, React",
#     "benefits": "Health insurance, 401k, Unlimited PTO, Equity",
#     "description": "Join our team to build...",
#     "posted_date": "January 3, 2026"
#   }
# }
# pip install webscraping_ai
# https://pypi.org/project/webscraping-ai/
from webscraping_ai import Client

client = Client(api_key="YOUR_API_KEY")
result = client.fields(
    "https://company.com/careers/senior-engineer",
    fields={
        "job_title": "Job title",
        "company": "Company name",
        "location": "Job location",
        "remote": "Is remote work available (yes/no/hybrid)",
        "salary_min": "Minimum salary if listed",
        "salary_max": "Maximum salary if listed",
        "experience_level": "Required experience level",
        "employment_type": "Full-time, part-time, contract, etc.",
        "required_skills": "Required skills, comma-separated",
        "benefits": "Benefits mentioned, comma-separated",
        "description": "Job description summary",
        "posted_date": "When the job was posted",
    },
)
print(result)
# Response:
# {
#   "result": {
#     "job_title": "Senior Software Engineer",
#     "company": "TechCorp",
#     "location": "San Francisco, CA",
#     "remote": "hybrid",
#     "salary_min": "150000",
#     "salary_max": "200000",
#     "experience_level": "5+ years",
#     "employment_type": "Full-time",
#     "required_skills": "Python, AWS, PostgreSQL, React",
#     "benefits": "Health insurance, 401k, Unlimited PTO, Equity",
#     "description": "Join our team to build...",
#     "posted_date": "January 3, 2026"
#   }
# }
// npm install webscraping-ai
// https://www.npmjs.com/package/webscraping-ai
import { WebScrapingAI } from 'webscraping-ai';

const client = new WebScrapingAI({ apiKey: 'YOUR_API_KEY' });
const result = await client.fields({
  url: 'https://company.com/careers/senior-engineer',
  fields: {
    job_title: 'Job title',
    company: 'Company name',
    location: 'Job location',
    remote: 'Is remote work available (yes/no/hybrid)',
    salary_min: 'Minimum salary if listed',
    salary_max: 'Maximum salary if listed',
    experience_level: 'Required experience level',
    employment_type: 'Full-time, part-time, contract, etc.',
    required_skills: 'Required skills, comma-separated',
    benefits: 'Benefits mentioned, comma-separated',
    description: 'Job description summary',
    posted_date: 'When the job was posted',
  },
});
console.log(result);
// Response:
// {
//   "result": {
//     "job_title": "Senior Software Engineer",
//     "company": "TechCorp",
//     "location": "San Francisco, CA",
//     "remote": "hybrid",
//     "salary_min": "150000",
//     "salary_max": "200000",
//     "experience_level": "5+ years",
//     "employment_type": "Full-time",
//     "required_skills": "Python, AWS, PostgreSQL, React",
//     "benefits": "Health insurance, 401k, Unlimited PTO, Equity",
//     "description": "Join our team to build...",
//     "posted_date": "January 3, 2026"
//   }
// }
<?php
// composer require webscraping-ai/webscraping-ai-php
// https://packagist.org/packages/webscraping-ai/webscraping-ai-php
require 'vendor/autoload.php';

use WebScrapingAI\Client;

$client = new Client('YOUR_API_KEY');
$result = $client->fields('https://company.com/careers/senior-engineer', [
    'job_title'        => 'Job title',
    'company'          => 'Company name',
    'location'         => 'Job location',
    'remote'           => 'Is remote work available (yes/no/hybrid)',
    'salary_min'       => 'Minimum salary if listed',
    'salary_max'       => 'Maximum salary if listed',
    'experience_level' => 'Required experience level',
    'employment_type'  => 'Full-time, part-time, contract, etc.',
    'required_skills'  => 'Required skills, comma-separated',
    'benefits'         => 'Benefits mentioned, comma-separated',
    'description'      => 'Job description summary',
    'posted_date'      => 'When the job was posted',
]);
print_r($result);
// Response:
// {
//   "result": {
//     "job_title": "Senior Software Engineer",
//     "company": "TechCorp",
//     "location": "San Francisco, CA",
//     "remote": "hybrid",
//     "salary_min": "150000",
//     "salary_max": "200000",
//     "experience_level": "5+ years",
//     "employment_type": "Full-time",
//     "required_skills": "Python, AWS, PostgreSQL, React",
//     "benefits": "Health insurance, 401k, Unlimited PTO, Equity",
//     "description": "Join our team to build...",
//     "posted_date": "January 3, 2026"
//   }
// }
# gem install webscraping_ai
# https://rubygems.org/gems/webscraping_ai
require 'webscraping_ai'

client = WebScrapingAI::Client.new(api_key: 'YOUR_API_KEY')
result = client.fields(
  'https://company.com/careers/senior-engineer',
  fields: {
    job_title:         'Job title',
    company:           'Company name',
    location:          'Job location',
    remote:            'Is remote work available (yes/no/hybrid)',
    salary_min:        'Minimum salary if listed',
    salary_max:        'Maximum salary if listed',
    experience_level:  'Required experience level',
    employment_type:   'Full-time, part-time, contract, etc.',
    required_skills:   'Required skills, comma-separated',
    benefits:          'Benefits mentioned, comma-separated',
    description:       'Job description summary',
    posted_date:       'When the job was posted',
  }
)
puts result.inspect
# Response:
# {
#   "result": {
#     "job_title": "Senior Software Engineer",
#     "company": "TechCorp",
#     "location": "San Francisco, CA",
#     "remote": "hybrid",
#     "salary_min": "150000",
#     "salary_max": "200000",
#     "experience_level": "5+ years",
#     "employment_type": "Full-time",
#     "required_skills": "Python, AWS, PostgreSQL, React",
#     "benefits": "Health insurance, 401k, Unlimited PTO, Equity",
#     "description": "Join our team to build...",
#     "posted_date": "January 3, 2026"
#   }
# }
// go get github.com/webscraping-ai/webscraping-ai-go/v4
// https://pkg.go.dev/github.com/webscraping-ai/webscraping-ai-go/v4
package main

import (
    "context"
    "fmt"

    webscrapingai "github.com/webscraping-ai/webscraping-ai-go/v4"
)

func main() {
    client, _ := webscrapingai.NewClient(&webscrapingai.Config{APIKey: "YOUR_API_KEY"})
    result, _ := client.Fields(context.Background(), &webscrapingai.FieldsOptions{
        URL: "https://company.com/careers/senior-engineer",
        Fields: map[string]string{
            "job_title": "Job title",
            "company": "Company name",
            "location": "Job location",
            "remote": "Is remote work available (yes/no/hybrid)",
            "salary_min": "Minimum salary if listed",
            "salary_max": "Maximum salary if listed",
            "experience_level": "Required experience level",
            "employment_type": "Full-time, part-time, contract, etc.",
            "required_skills": "Required skills, comma-separated",
            "benefits": "Benefits mentioned, comma-separated",
            "description": "Job description summary",
            "posted_date": "When the job was posted",
        },
    })
    fmt.Println(result.Result)
}
// Response:
// {
//   "result": {
//     "job_title": "Senior Software Engineer",
//     "company": "TechCorp",
//     "location": "San Francisco, CA",
//     "remote": "hybrid",
//     "salary_min": "150000",
//     "salary_max": "200000",
//     "experience_level": "5+ years",
//     "employment_type": "Full-time",
//     "required_skills": "Python, AWS, PostgreSQL, React",
//     "benefits": "Health insurance, 401k, Unlimited PTO, Equity",
//     "description": "Join our team to build...",
//     "posted_date": "January 3, 2026"
//   }
// }
// Maven: ai.webscraping:webscraping-ai:4.2.0
// https://central.sonatype.com/artifact/ai.webscraping/webscraping-ai
import ai.webscraping.Client;
import ai.webscraping.Config;
import ai.webscraping.option.FieldsOptions;
import ai.webscraping.result.FieldsResult;

Client client = new Client(Config.builder().apiKey("YOUR_API_KEY").build());
FieldsResult result = client.fields(FieldsOptions.builder()
    .url("https://company.com/careers/senior-engineer")
    .addField("job_title", "Job title")
    .addField("company", "Company name")
    .addField("location", "Job location")
    .addField("remote", "Is remote work available (yes/no/hybrid)")
    .addField("salary_min", "Minimum salary if listed")
    .addField("salary_max", "Maximum salary if listed")
    .addField("experience_level", "Required experience level")
    .addField("employment_type", "Full-time, part-time, contract, etc.")
    .addField("required_skills", "Required skills, comma-separated")
    .addField("benefits", "Benefits mentioned, comma-separated")
    .addField("description", "Job description summary")
    .addField("posted_date", "When the job was posted")
    .build());
System.out.println(result.getResult());
// Response:
// {
//   "result": {
//     "job_title": "Senior Software Engineer",
//     "company": "TechCorp",
//     "location": "San Francisco, CA",
//     "remote": "hybrid",
//     "salary_min": "150000",
//     "salary_max": "200000",
//     "experience_level": "5+ years",
//     "employment_type": "Full-time",
//     "required_skills": "Python, AWS, PostgreSQL, React",
//     "benefits": "Health insurance, 401k, Unlimited PTO, Equity",
//     "description": "Join our team to build...",
//     "posted_date": "January 3, 2026"
//   }
// }
// dotnet add package WebScrapingAI
// https://www.nuget.org/packages/WebScrapingAI
using WebScrapingAI;

var client = new WebScrapingAIClient(new WebScrapingAIClientOptions { ApiKey = "YOUR_API_KEY" });
var result = await client.FieldsAsync(new FieldsRequest {
    Url = "https://company.com/careers/senior-engineer",
    Fields = new Dictionary<string, string> {
        ["job_title"] = "Job title",
        ["company"] = "Company name",
        ["location"] = "Job location",
        ["remote"] = "Is remote work available (yes/no/hybrid)",
        ["salary_min"] = "Minimum salary if listed",
        ["salary_max"] = "Maximum salary if listed",
        ["experience_level"] = "Required experience level",
        ["employment_type"] = "Full-time, part-time, contract, etc.",
        ["required_skills"] = "Required skills, comma-separated",
        ["benefits"] = "Benefits mentioned, comma-separated",
        ["description"] = "Job description summary",
        ["posted_date"] = "When the job was posted",
    },
});
Console.WriteLine(result.Result);
// Response:
// {
//   "result": {
//     "job_title": "Senior Software Engineer",
//     "company": "TechCorp",
//     "location": "San Francisco, CA",
//     "remote": "hybrid",
//     "salary_min": "150000",
//     "salary_max": "200000",
//     "experience_level": "5+ years",
//     "employment_type": "Full-time",
//     "required_skills": "Python, AWS, PostgreSQL, React",
//     "benefits": "Health insurance, 401k, Unlimited PTO, Equity",
//     "description": "Join our team to build...",
//     "posted_date": "January 3, 2026"
//   }
// }

Benefits of Job Data

Build Job Boards: Aggregate listings from multiple sources into one platform.
Salary Research: Analyze compensation data across roles and locations.
Market Intelligence: Track hiring trends by industry and skill.
Competitive Intel: Monitor competitor hiring and growth.
Skills Analysis: Identify in-demand skills and technologies.

Use Cases

Job Board Aggregation

Build comprehensive job search platforms

Salary Benchmarking

Research market rates for HR and recruiting

Hiring Trend Analysis

Track job market health and growth sectors

Skills Gap Research

Identify emerging skill requirements

Related Use Cases

More data aggregation solutions

Lead Generation

Extract company data for recruiting.

Alternative Data

Use hiring signals for investment analysis.

CRM Enrichment

Enrich candidate and company profiles.

Start Aggregating Job Data

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