The Job Postings API provides programmatic access to the largest publicly available dataset of US job postings, with over 2.2 million total listings and 1.6 million currently active roles. This API is designed for developers, data analysts, and talent intelligence teams who need structured, real-time job market data. Its core value lies in offering rich company-level records—including median compensation, salary ranges, work model distributions, department breakdowns, and hiring momentum—all compiled directly from the API's own data. By delivering this depth without requiring web scraping or manual aggregation, the API saves countless hours and ensures data accuracy for downstream applications.
The primary pain point this API solves is the difficulty of obtaining clean, granular, and up-to-date job posting data at scale. Traditional approaches involve scraping dozens of career pages and Applicant Tracking Systems, each with different schemas and rate limits, resulting in incomplete or stale data. Researchers and recruiters need to know not just which jobs exist, but also how companies are hiring—by department, location, salary band, and remote policy. Without a unified API, comparing hiring trends across employers or identifying high-salary roles in specific cities requires enormous manual effort. The Job Postings API eliminates these barriers by offering a single endpoint with consistent, normalized data.
The first major feature group is the detailed company record snapshot. For any company tracked in the API, users can retrieve an all-time posting count, new postings this week, median posted compensation, salary range, and work model breakdown (on-site, hybrid, remote). This data is further segmented by roles by function (e.g., Engineering, Research, Go-to-Market) and top locations (e.g., San Francisco, New York, Seattle). Such granularity enables users to quickly assess a company's hiring structure without browsing job boards. The benefit is immediate competitive intelligence: for example, seeing that a company has shifted to 40% remote roles can inform talent strategy or market analysis.
The second major feature group is the hiring momentum tracker, which shows changes over the last 30 days per department. The API exposes real-time hiring velocity—whether a company is scaling research (+42 roles), doubling its GTM team (+28), or slowing support (−12). This feature is critical for understanding where a company is investing headcount and where layoffs or freezes are occurring. Additionally, the API tracks top technologies and SaaS tools mentioned across job descriptions, such as Python, PyTorch, Kubernetes, and Salesforce. This allows users to infer technology stacks and tooling preferences, which is valuable for competitive analysis, vendor research, and skills gap assessments.
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The third feature group encompasses ATS-level tracking and lifecycle events. The API monitors all major Applicant Tracking Systems, including Greenhouse, Lever, Workday, Ashby, iCIMS, BambooHR, and over 30 others. Users can filter job postings by ATS provider to see which companies publish through a specific platform. More powerfully, the API supports streaming job lifecycle events: roles opened, updated, and closed in near real-time. This enables users to build dashboards that track job openings as they happen, identify newly posted roles before competitors, and detect when a company is backfilling positions. The combination of ATS coverage and event streaming makes the API a comprehensive tool for real-time hiring intelligence.
The API works by providing RESTful endpoints that return JSON data. Users can query by company domain (e.g., openai.com) to pull every active job posting for that employer. Results can be filtered by department, city, remote policy, salary range, and other fields. The workflow is intuitive: authenticate with an API key, construct a request with relevant parameters, and receive structured data with rich metadata. For advanced use cases, the streaming endpoint delivers a feed of role lifecycle events, enabling integrations with analytics pipelines or alerting systems. The API's data is updated continuously, with over 23,000 new postings added daily, ensuring users always have the freshest perspective on the US job market.
Concrete use cases include looking up OpenAI by domain and pulling every active posting, breaking down Stripe's roles by department and city, or finding all software engineering roles in New York with a base salary above $200K. Another scenario is streaming Databricks' job lifecycle events to monitor when roles open and close. Users can also compare remote, hybrid, and on-site shares across multiple companies like Stripe, Anthropic, and Databricks, or identify which companies publish through a specific ATS such as Greenhouse. The outcomes are faster market research, improved competitive analysis, and data-driven talent acquisition strategies. For example, a recruiting team can spot that a competitor is aggressively hiring engineers in San Francisco and adjust their own sourcing accordingly.
The target audience includes talent acquisition teams, HR analysts, market researchers, data scientists, and developers building recruitment tools or labor market analytics platforms. The API supports both free and enterprise tiers: the free tier offers 100 requests per second with a 500 burst limit, while the enterprise tier provides unlimited throughput upon request. It integrates seamlessly with Python, JavaScript, and any language capable of making HTTP requests. The platform itself is web-based with comprehensive documentation and a docs page for AI. Ultimately, the Job Postings API empowers anyone who needs real-time, granular US job data to make faster, more informed decisions about hiring, investment, and workforce planning.
Recruiters, talent acquisition teams, HR analysts, market researchers, data scientists tracking labor market trends, hiring managers, and developers building job aggregation tools or analytics dashboards. The API is ideal for anyone needing real-time, structured US job posting data—from a sole practitioner running competitive salary analysis to a large enterprise monitoring hiring velocity across hundreds of companies. It also serves investors and venture capitalists who require granular hiring signals to assess company growth phases.