How Recruiters Search ATS (2026): Filters, Keywords, and Boolean

Quick answer

Write for search: use the same terms as the job post, keep them in plain text, and prove them in bullets.

Recruiters commonly search the candidate database using keywords (job titles, skills, locations) and narrow with filters. If your “keywords” are trapped inside icons, text boxes, tables, or images, they may not be searchable.

What this means for you: you don’t need tricks—you need searchable, standard wording (and clear proof).

The recruiter search model

The ATS stores your resume and (usually) extracts text from it.
Recruiters search for keywords (skills, titles, tools) and see matching candidates.
Recruiters filter results (location, education, stage, referral, etc.) to prioritize a shortlist.

Exact match vs “close enough”

Some ATS filtering tools require an exact keyword match in the application text. If the job calls for “Tableau,” writing “dashboard tools” is weaker for search.

Better

“Built Tableau dashboards and automated weekly KPI reporting.”

Weaker

“Created dashboards and reports.”

Boolean search (AND / OR / NOT / quotes)

Some ATS platforms support Boolean queries (AND/OR/NOT), phrase search with quotes, and wildcards like*. This is why using the right exact terms helps.

Examples recruiters might use:

engineer AND "senior developer"
trainer OR instructor OR teacher
Java* (to match Java / Javascript variations)

Where to place keywords (best spots)

Best placement order

Experience bullets: highest credibility (keyword + proof + metric).
Skills section: fast scan, but should be backed by bullets.
Summary: only the most important 2–4 terms (avoid stuffing).

Be-findable checklist

Copy/paste this

I used the exact tool names and role terms from the posting (when true).
Key terms appear in Experience bullets with proof (scope/metrics).
No columns/tables/text boxes/icons that could hide keywords from parsing.
I included acronym + full form once (e.g., “ETL (extract, transform, load)”).

Sources

Greenhouse Support: “Search candidates using Boolean queries” (AND/OR/NOT, phrase search, wildcards). View source
Greenhouse Support: “Talent Filtering” (keyword search; required vs preferred terms; exact match requirement; filters). View source
Greenhouse Support: “Search resumes for keywords” (full text search and keyword snippets). View source