🐒 Welcome to the Jungle (WTTJ) Jobs Scraper: Salary and RAG Data

Extract Welcome to the Jungle tech jobs as raw JSON or RAG-ready chunks. Salary ranges, remote policy, and contract type across France, UK, US, Germany, and 50+ countries, ready for spreadsheets or vector databases.
Global technology and remote hiring   •  Hacker News Hiring, GoFractional, NoFluffJobs, and Welcome to the Jungle tech roles
HN Hiring Structured jobs from HN threads	GoFractional Fractional jobs, direct ATS links	NoFluffJobs European tech jobs and salaries	WTTJ ➤ You are here

Welcome to the Jungle (WTTJ) jobs: salary, location, and RAG-ready data Job listings with salary ranges, remote policy, contract type, and company details across France, UK, US, Germany, and 50+ countries. Export clean JSON or pre-chunked text for vector databases.

🔀 Dual output modes Raw JSON for pipelines, RAG-ready chunks for AI agents

🧩 Framework ready Drops into LangChain, LlamaIndex, Pinecone, or Qdrant

🌍 Europe plus US coverage France, UK, Germany, Spain, and 50+ countries

🔓 No auth required Public Algolia API, no login or API key needed

Extract job listings from Welcome to the Jungle (WTTJ) with two output modes: raw JSON or RAG-ready chunks. Get salary ranges, company data, locations, contract type, and remote policy across France, UK, US, Germany, and 50+ countries. Drop raw output into spreadsheets or pipelines. Use RAG-ready chunks directly in Qdrant, Pinecone, Weaviate, LangChain, or LlamaIndex for AI-powered job matching and resume screening. No login or API key needed.

🔍 What does Welcome to the Jungle Scraper do?

This Actor queries WTTJ's public Algolia search API to extract structured job data. It supports two output modes:

1. Raw JSON - Full job listings with title, company, salary, locations, contract type, remote policy, summary, and sectors. Ready for spreadsheets, CRMs, or data warehouses.

2. RAG-Ready - Job descriptions tokenized into fixed-size chunks using tiktoken cl100k_base. Configurable chunk size (default 512 tokens) with overlap. Drop straight into any vector database for LLM-based job matching, resume screening, or market intelligence.

The scraper covers 10,000+ companies across Europe and the US. No login, no API key, no proxy required.

💡 Why use Welcome to the Jungle Scraper for RAG?

• Dual output modes. Raw JSON for traditional pipelines, RAG-ready chunks for AI agents and vector databases. One Actor handles both workflows.
• RAG-ready chunks. Job descriptions pre-split for LLM ingestion. No LaTeX stripping, no HTML parsing, no custom chunking logic on your side. Works with Qdrant, Pinecone, Weaviate, pgvector, and Chroma.
• Framework-ready. Raw output drops into Google Sheets, BigQuery, n8n, or any CRM. RAG chunks drop into LangChain, LlamaIndex, Haystack, or custom LLM pipelines.
• Europe plus US coverage. France, UK, Germany, Spain, and 50+ countries in one query. Compare salary ranges across markets.
• Rich job metadata. Salary ranges (EUR, GBP, USD), remote policy, contract type, experience level, company size, and hiring velocity.
• No auth required. Uses WTTJ's public Algolia API. No cookies, no API key, no account.

🚀 How to use Welcome to the Jungle Scraper

STEP 1 Set your search Enter a query like data engineer, product manager, or sales.

STEP 2 Choose output mode Pick raw for standard JSON or rag for chunked text.

STEP 3 Filter and run Add country, contract type, or remote policy filters, then export.

📥 Input

Field	Type	Required	Description
query	string	Yes	Job title, skill, or keyword to search.
locale	enum	No	Language index to search: en or fr. Default: en.
countryCodes	array of strings	No	Filter by country codes (e.g., FR, GB, US).
locations	array of strings	No	Filter by city or region (e.g., Paris, London).
contractTypes	array of strings	No	Filter by contract type (full_time, part_time, internship, freelance, apprenticeship, vie).
remotePolicies	array of strings	No	Filter by remote policy (full, partial, punctual, no).
categories	array of strings	No	Filter by job category (tech, data, sales, marketing).
includeJobDetails	boolean	No	Fetch the full candidate profile text for each listing. Default: false.
outputMode	enum	Yes	raw for full JSON or rag for chunked text. Default: raw.
chunkSize	integer	No	Target tokens per chunk in RAG mode. Default: 512.
chunkOverlap	integer	No	Token overlap between chunks in RAG mode. Default: 50.
maxItems	integer	Yes	Maximum jobs to return. Default: 100.
proxyConfiguration	object	No	Proxy settings for the run. Defaults to Apify Proxy.

📤 Output

Raw Mode Example

{
    "jobId": "2d4fbe25-352d-47a4-8280-bd6d4642cfb1",
    "slug": "data-analytics-engineer-visian-xxx",
    "title": "Data analytics engineer",
    "contractType": "full_time",
    "remotePolicy": "partial",
    "publishedAt": "2026-06-04T09:39:54Z",
    "experienceMin": 3,
    "educationLevel": "master",
    "profession": {
        "name": "Data analyst",
        "category": "Data"
    },
    "company": {
        "name": "Visian",
        "slug": "visian",
        "size": "50-249 employees",
        "employeeCount": 200,
        "description": "Consulting et execution technique pour projets data.",
        "sectors": ["Artificial Intelligence / Machine Learning", "IT / Digital"]
    },
    "locations": [
        { "city": "Courbevoie", "country": "France", "countryCode": "FR", "region": "Ile-de-France" }
    ],
    "primaryLocation": "Courbevoie, France",
    "salary": {
        "hasSalary": true,
        "min": 42000,
        "max": 55000,
        "yearlyMinimum": 42000,
        "currency": "EUR",
        "period": "yearly"
    },
    "summary": "Rejoignez Visian, une societe de conseil specialisee en innovation...",
    "benefits": ["Remote work", "Health insurance"],
    "applyUrl": "https://www.welcometothejungle.com/en/jobs/data-engineer-visian-xxx/apply",
    "url": "https://www.welcometothejungle.com/en/jobs/data-engineer-visian-xxx",
    "scrapedAt": "2026-06-06T10:00:00.000Z"
}

RAG Mode Example

{
    "jobId": "2d4fbe25-352d-47a4-8280-bd6d4642cfb1",
    "title": "Data analytics engineer",
    "company": { "name": "Visian", "slug": "visian" },
    "primaryLocation": "Courbevoie, France",
    "salary": { "hasSalary": true, "min": 42000, "max": 55000, "currency": "EUR" },
    "chunks": [
        { "idx": 0, "text": "Job Title: Data analytics engineer\nCompany: Visian\nLocation: Courbevoie, France\n\nRejoignez Visian...", "tokens": 256 },
        { "idx": 1, "text": "...SQL, Databricks, Git et Power BI...", "tokens": 128 }
    ],
    "scrapedAt": "2026-06-06T10:00:00.000Z"
}

RAG mode drops the summary field and replaces it with chunks. Every other field from raw mode is still present.

📊 Data Table

Field	Type	Description
jobId	string	WTTJ unique job identifier.
slug	string	Job URL slug.
title	string	Job title as posted.
contractType	string	Contract type code (full_time, part_time, internship, freelance, apprenticeship, vie).
remotePolicy	string	Remote work policy (full, partial, punctual, no).
publishedAt	string	ISO date the job was published.
experienceMin	integer	Minimum years of experience required, when disclosed.
educationLevel	string	Minimum education level required, when disclosed.
profession	object	Job classification: name and category.
company	object	Employer details: name, slug, url, logo, size, employeeCount, description, sectors.
locations	array	Location objects with city, country, countryCode, region.
primaryLocation	string	Primary location as a formatted string.
salary	object	Salary details: hasSalary, min, max, currency, period.
summary	string	Short job summary. Raw mode only.
profile	string	Candidate profile or requirements text, when includeJobDetails is enabled.
benefits	array	Listed job benefits, when disclosed.
applyUrl	string	Direct application URL, when available.
url	string	Canonical job URL on welcometothejungle.com.
chunks	array	RAG mode only: array of { idx, text, tokens } chunks replacing summary.
scrapedAt	string	ISO timestamp of extraction.

💰 Pricing

Pay per result. You are billed only for job listings successfully saved to your dataset. An empty run costs nothing, and there is no subscription or minimum spend. See the Actor's Pricing tab in Apify Console for the current rate.

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🛠️ Tips

• Use RAG mode for AI agents. Feed chunks directly into a vector database for job matching, resume screening, or market intelligence. Compatible with LangChain, LlamaIndex, Qdrant, Pinecone, and Weaviate.
• Filter by country first. WTTJ has different job densities per market. France and UK have the most listings.
• Combine with salary filters. Many jobs disclose salary ranges. Filter salary.hasSalary: true downstream for benchmarking.
• Schedule weekly for market tracking. Compare job counts and salary ranges over time to detect hiring trend shifts.

❓ FAQ, Disclaimers, and Support

Is scraping Welcome to the Jungle legal? This Actor uses WTTJ's public Algolia search API, which requires no authentication. It collects publicly visible job listing data for research, market analysis, and recruiting intelligence. Users are responsible for ensuring their use complies with applicable laws and WTTJ's terms of service.

Why are some salary fields empty? Many jobs on WTTJ do not disclose salary. The Actor only saves salary values that the source exposes. Filter salary.hasSalary: true downstream if salary data is critical.

What is RAG mode? RAG (Retrieval-Augmented Generation) mode splits job descriptions into fixed-token chunks using tiktoken cl100k_base encoding. These chunks are ready to embed and store in a vector database for LLM-based job matching or resume screening.

How is this different from other WTTJ scrapers? This is the only WTTJ scraper with dual output modes: raw JSON for traditional pipelines and RAG-ready chunks for AI agents. No other scraper offers tiktoken-based chunking optimized for LLM ingestion.

Support: Open an issue on the Actor's Issues tab in Apify Console for bug reports, feature requests, or custom-run quotes.

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