Lever resume format and parsing guide

Lever's homepage FAQ calls it an applicant tracking system (ATS) and recruiting CRM, and the page is branded "Lever by Employ". (Lever) Employers buy it to post jobs and manage candidates; each sets up its own application form and questions.

1. Open the posting and click Apply. The form is usually one page.
2. Attach your resume first. On the Palantir form we looked at, the page shows "Analyzing resume..." and fills in fields, or shows "Couldn't auto-read resume." if it can't. (Palantir job site (Lever))
3. Check the fields. That form asked for full name, email, phone, current location (required), current company, LinkedIn, GitHub and portfolio links, then the employer's own questions, such as work authorisation and sponsorship.
4. Submit. The employer reviews applications in Lever.

Lever's developer documentation describes resume parsing when a candidate is created through its API. With parsing on and a resume file supplied, "the resume will be parsed and extracted data will be used to autofill information about the contact". The fields it lists are name, headline, emails, phones, location, company and links, "although no information is guaranteed to be extracted". (Lever)

The same documentation says "image files are not supported and will not be successfully parsed for information", and that fields supplied directly take precedence over parsed data.

1. Attach a text-based file. Never a photo or scan of your resume: Lever's documentation says image files are not parsed.
2. Put city and country in your contact line. Location is one of the parsed fields, and the form we looked at required a current location.
3. Make your current job easy to find. Company is a parsed field and the form asks for your current company: put your latest title and employer at the top of your experience.
4. Write links out in full. Links are parsed too. "linkedin.com/in/yourname" is clearer to software than an icon.
5. If it says "Couldn't auto-read resume". Type the fields yourself. Either way, check what was filled in before you submit.

In a study dated 9 October 2026, we exported 21 PDFs from Resumity's 7 templates and read them back with three open-source text extractors, pdf.js, pdftotext and pypdf (63 extractions). Every name, email, phone number, section heading and bullet came back intact and in order. That tells you the text layer of those PDFs is complete.

It does not tell you how Lever reads the same file. We have not tested Resumity's templates in Lever, and each employer configures its own setup. The method, limits and raw data are on how we test our templates.