Most ATS advice is written for systems that filter before a human ever sees you — platforms where an algorithm scores your resume against a job description and you either clear a threshold or you don't. Lever doesn't work that way.
There's no automated scoring gate. A recruiter searches the candidate database using keywords, pulls up the results, and reads the resumes that surface. Which means two things matter that most candidates aren't optimizing for: whether your resume surfaces in the search at all, and whether it holds up when someone actually reads it.
Understanding how Lever works — specifically how it searches, what it can and can't parse, and how recruiters interact with applications — changes what good preparation looks like.
What Lever Is
LeverTRM is an applicant tracking system combined with a candidate relationship management platform, used by mid-size and growth-stage companies across tech and professional services. Lever was acquired by Employ Inc. in 2022, joining a suite that includes Jobvite and JazzHR.
The platform was designed around recruiter workflow rather than algorithmic filtering. It includes a feature called Talent Fit that provides AI-assisted candidate ranking as a tool for recruiters — surfacing strong matches from a candidate pool — but this operates on the recruiter's side. It is not an automated filter that eliminates candidates before a human reviews their application.
That distinction matters. When you apply through Lever, you're not being scored against a pass/fail threshold. You're entering a database that a recruiter will search, and a document they will read.
How a Lever Application Actually Works
Lever's application form is deliberately minimal: contact information and a file upload. There is no lengthy structured questionnaire to fill out before your resume is seen (though some employers add knockout questions through Lever's Advanced Automation features — more on that below).
When you upload your resume, Lever parses it into a structured candidate profile, extracting your name, work history, job titles, education, skills, and contact details. This parsed profile populates a candidate card — the view a recruiter sees when reviewing applicants. Your original uploaded document is accessible alongside this card as an attachment.
Recruiters use a feature called Fast Resume Review to work through incoming applications: a sprint-style sequence where they move candidates forward, skip, or archive based on what they see. The parsed card is their first interaction with your application. Your actual document is what they read when they want more.
How candidates get found in the first place is through keyword search. Lever's search allows recruiters to filter by job title, skills, experience, location, and other qualifications — pulling from both the parsed profile fields and the full text of your resume. Getting found requires that the right terms appear in your document. Getting considered requires that the document is worth reading once they do.
The Abbreviation Problem
This is the most important Lever-specific thing in this guide, and the most commonly overlooked.
Lever's search supports word stemming — searching for "manage" returns results containing "managed," "managing," and "management." That's helpful. But Lever's search does not expand abbreviations or acronyms. This is confirmed in Lever's own search documentation.
What that means in practice: if a recruiter searches for "Search Engine Optimization," your profile will not appear if your resume only says "SEO." The reverse is equally true — a search for "SEO" will not find a resume that only spells it out. They are different strings to Lever's search engine, and neither retrieves the other.
This creates an invisible findability gap. You may be exactly the right candidate. Your resume may parse cleanly and read well. But if a recruiter searches using the form you didn't include, you don't surface.
The fix is simple: include both forms wherever a term appears in either form in the job description.
This applies most consequentially to:
- Credentials and certifications — "Project Management Professional (PMP)," "Certified Public Accountant (CPA)," "Certified Information Systems Security Professional (CISSP)"
- Technologies and tools — "Machine Learning (ML)," "Artificial Intelligence (AI)," "Natural Language Processing (NLP)"
- Methodologies — "Continuous Integration/Continuous Deployment (CI/CD)," "Object-Oriented Programming (OOP)"
- Common role-specific shorthand — whatever abbreviations appear in the job posting itself
The easiest way to handle this: when you first introduce a term, write it out in full with the abbreviation in parentheses — the same convention used in formal writing. After that, either form is fine. What you cannot do is use only one form and assume the other will be found.
Want to check whether your resume has abbreviation gaps against this job posting? RigTheResume analyzes your resume against any Lever job description and flags where terms appear in only one form — along with your overall match score and platform-specific tips. Analyze your resume free →
Formatting: What Survives the Parse
Because the parsed candidate card is a recruiter's first view of your application, parse quality matters. Errors in parsing don't just affect keyword search — they affect what the recruiter sees when they pull up your profile.
Lever cannot parse images. If any part of your resume is embedded as an image — a graphical header, a logo, a skill bar chart, contact details inside a styled banner — that content will not be extracted. A resume where the name and contact information appear only in an image header is a resume where Lever has no name or contact details for the candidate. This is more common than it sounds, especially with visually designed resume templates.
Columns and tables may cause formatting issues. Lever's own documentation notes that while it can attempt to parse columns and tables, the format can sometimes be affected. Single-column layouts are the safest approach for reliable extraction.
Contact information must be in the document body. Headers and footers are frequently missed by the parser. Your name, email, phone number, and LinkedIn URL should appear in the main text of the document, not in a styled header or footer section.
Accepted formats: PDF, Word (.docx), RTF, HTML, and Open Office (ODF). Text-based PDFs and .docx files are the most reliable choices. A resume saved as an image-based PDF — common with some design tools — will not parse at all.
A practical test: paste your resume text into a plain text editor. Everything that appears there is parseable. Everything that doesn't — any content that lives only in images, headers, footers, or text boxes — will not be extracted by Lever.
Keywords and Full-Text Search
Lever indexes the full text of your resume, not just the structured fields the parser extracts. This means every word in your document is searchable — including terms in your experience bullets, your summary, and anywhere else in the document.
The practical implication: don't silo your important keywords in a Skills section and leave them out of your experience description. A skill that appears only in a list at the top of your resume is searchable, but a skill that appears in your Skills section and again naturally in an experience bullet is more credibly represented — and more likely to surface across different search approaches.
Mirror the job description's language where it accurately describes your experience. Not to satisfy a semantic matching algorithm — Lever's search is more literal than semantic — but because recruiters search using the terms they put in the job posting. If the posting says "product-led growth" and your resume says "PLG," only one of you is using the form the recruiter is likely to search for.
The Part Most ATS Guides Miss: Your Resume Gets Read
Because Lever's review is human-forward, the document quality matters in a way it doesn't on more algorithmic platforms. On Taleo or iCIMS, a resume can score well purely on keyword density while being nearly unreadable as a document. On Lever, a recruiter is going to open your PDF and read it.
That means the things that make a resume readable to a person — a clear professional summary that establishes who you are quickly, well-structured experience bullets that lead with outcomes, logical flow from role to role — aren't just nice to have. They're part of what gets you moved forward rather than archived.
This isn't an argument for sacrificing keyword coverage in favor of beautiful prose. It's an argument for not treating those as a trade-off. The resume that works best in Lever is one that surfaces correctly in a keyword search and then delivers something worth reading when a recruiter clicks through.
A Pre-Submission Checklist
Before submitting any application through Lever:
Parsing
- No image-based content — name, contact details, and all resume text appear as parseable text, not embedded graphics
- Contact information in the document body, not a header or footer
- Single-column layout, or confirmed that your layout parses cleanly as plain text
- Saved as text-based PDF or .docx — not an image PDF
Keywords
- Every term that appears as an abbreviation or acronym in the job description also appears in full form in your resume — and vice versa
- Key skills appear in both a Skills or Core Competencies section and naturally within experience bullets
- Language mirrors the job posting's terminology where it accurately describes your experience
Document quality
- Professional summary establishes your identity and level quickly
- Experience bullets lead with outcomes, not duties
- The resume reads clearly as a document, not just as a keyword container
One More Thing: Knockout Questions
Some employers using Lever's Advanced Automation features add knockout questions to their application flow — yes/no or short-answer questions that appear before or alongside the resume upload. These vary by employer and are not a standard Lever feature, but if you encounter them, treat them seriously.
A knockout question answered carelessly can eliminate an otherwise strong application before Fast Resume Review begins. Answer accurately, completely, and in the language of the job posting.
The Bottom Line
Lever rewards candidates who are findable and readable. Findable means your resume contains the right terms — in both abbreviated and spelled-out form — in the right places. Readable means that when a recruiter surfaces your profile and opens your document, what they find is worth their time.
The abbreviation gap is the most common way qualified candidates become invisible in Lever. The formatting issues are the most common way resumes parse badly and create a poor first impression at the card view. Get both right, and Lever's human-forward model works in your favor — your resume actually gets read on its merits.
See How Your Resume Performs in Lever
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