Random job posting generator
This tool builds fake but realistic job postings for filling job boards, recruiting dashboards, and applicant-tracking demos. Each posting includes the fields a real vacancy needs so your UI can be tested against complete records.
How it works
The generator picks a role and a seniority prefix to form the title, a fictional company name, a location, and an employment type. A salary range is generated as two random values a sensible distance apart, formatted with a currency symbol. Three to five requirements are drawn without repetition from a skills pool, and a short description is assembled from template sentences. Every field is independent so the combinations are effectively unlimited.
What each generated posting contains
A single output record includes:
| Field | Example |
|---|---|
| Job title | Senior Data Engineer |
| Company name | Fictional company (Vantex Solutions, Orbis Corp, etc.) |
| Location | City and region or remote |
| Employment type | Full-time, part-time, contract, or freelance |
| Salary range | Two plausible figures with a sensible spread |
| Requirements | 3–5 skill or experience requirements |
| Description | A short paragraph describing the role |
The JSON export formats these as an array of objects with consistent field names, ready for direct insertion into a fixture file or database seed script.
Practical uses for developers and recruiters
Building a job board from scratch — A new platform needs data before it is live so you can demo features, check layouts, and test search behaviour. Thirty generated postings give you enough to see whether pagination breaks, whether salary-range filters work correctly, and whether the search index handles skill keywords across titles and descriptions.
Testing applicant-tracking systems — ATS platforms need job posting records to test pipeline stages: applying, screening, shortlisting, interviewing, offering. Fake postings allow you to run through the full workflow without creating real vacancies that could confuse real applicants.
UI and UX mockups — Placeholder copy matters for design work. Generic “Job Title” labels look nothing like real listings; a generated posting with a realistic title, multi-line description, and specific salary range lets designers and stakeholders evaluate layouts against content that resembles production.
Demonstrating search and filtering — If you are building or evaluating full-text search or filter UIs, you need a corpus where the queries actually return varied results. A batch of 50–100 generated postings with diverse titles and requirement tags provides that corpus quickly.
Load testing and performance benchmarking — A job board storing 100,000 postings in production will behave differently than one with 10. Generating a large batch of JSON records and loading them into a test database lets you evaluate query performance at realistic scale before launch.
Tips for getting the most out of the generator
- Generate in batches of 20–50 when seeding a database. Smaller batches miss edge cases in pagination and filtering; very large single batches can be slow to copy from the browser.
- Use the JSON export rather than the readable text version for any technical task. The structured JSON maps directly to a database schema or fixture format.
- Check salary ranges manually if your platform has currency or locale-specific formatting rules. The generated ranges are plausible but generic; you may need to normalise them to match your expected data format.
- Do not publish generated postings to real candidates. The job titles and requirements are plausible but the companies are fictional and the roles do not exist. Generated data is for internal development and testing only.
- Replace description text for stakeholder demos if the placeholder sentences feel too generic. The structure and field set will be realistic even if you swap in real copy for a polished presentation.