Search Greenhouse, Lever and Ashby Jobs in One Place

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How to search Greenhouse, Lever and Ashby jobs in one place

A company's own careers page is the source of its job postings, and that page usually runs on a hiring platform such as Greenhouse, Lever, Ashby or Workday. Job boards copy the posting from there, and a copy can stay up after the original has closed. So the freshest place to look for a job is the company career pages themselves. The trouble is that there are thousands of them, and no single search box covers them all. This post shows two ways to search Greenhouse, Lever and Ashby jobs in one place: With Google and the site: operator, which is free and takes some work. With JobBloom, an AI job search engine I built to do the same thing in one sentence. Method 1: Google with the site: operator Each hiring platform hosts its customers' job pages on one domain. If you limit a Google search to that domain, you search every company on the platform at once. Platform Domain to search Greenhouse boards.greenhouse.io, job-boards.greenhouse.io Lever jobs.lever.co Ashby jobs.ashbyhq.com Workable apply.workable.com SmartRecruiters jobs.smartrecruiters.com A search for remote backend jobs on the first three looks like this: (site:boards.greenhouse.io OR site:job-boards.greenhouse.io OR site:jobs.lever.co OR site:jobs.ashbyhq.com) "backend engineer" (TypeScript OR "Node.js") remote
This works, and it's worth knowing. It also has four problems: Many results are closed. Google keeps a page in its index after the job is taken down. You only find out when you click. "Remote" is just a word. A posting that says "this role is not remote" matches the search as well as a remote job does. There is no ranking by fit. You get pages that contain your words, in Google's order, and you read each one to see if it suits you. The query gets long. Every platform you add is another site: clause, and Google limits a search to 32 words. Method 2: describe the job in one sentence JobBloom runs the same kind of search for you. You describe the job in plain English, and it searches company career pages on 33 hiring platforms. It's free and needs no sign-up. I typed "Remote backend engineer jobs, TypeScript or Node.js" on 15 November 2026. This is what came back: The search returned six open jobs. The top three were a Senior Backend Engineer (Node.js) role at Nuitée with a 95% match, a Senior Backend Engineer role at Ora So with 92%, and a TypeScript role at Databento with 88%. Each result has a short summary, skill tags, the location, and the hiring platform the posting came from. "View role" opens the original posting on the company's own page. You can also choose which platforms to search. All 33 are on by default: How the search works The pipeline has five steps. The loading screen groups them into three stages and updates as they run: 1. Understand the sentence An LLM reads the prompt and pulls out the hard requirements: the role, the location, whether the job is remote, hybrid or on-site, the job type, and the must-have skills. It then writes a short search query. You can see that query on the results page, next to "Searched for". 2. Search career pages only The query goes to a web search API, limited to the domains of the supported hiring platforms. This is the site: trick from method 1, applied to 33 platforms at once. Each platform is a small config entry: export const approvedJobHostFamilies = [
{
provider: 'greenhouse',
queryHost: 'boards.greenhouse.io',
hosts: [
'boards.greenhouse.io',
'job-boards.greenhouse.io',
'job-boards.eu.greenhouse.io',
'boards.eu.greenhouse.io',
],
},
{
provider: 'lever',
queryHost: 'jobs.lever.co',
hosts: ['jobs.lever.co', 'jobs.eu.lever.co'],
},
// ...31 more
]
Because the search is limited to these domains, job boards and reposts never enter the results. 3. Rank cheaply before any AI reads a page LLM calls are the expensive part of a search, so results first get a ranking from free signals: title match, location and age. Only the most promising ones go on to t...

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