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Brad Mayes — 18 websites ranked by shared content topics, category and on-page relevance.

Each result shows its full tech stack, contacts and AI-policy — not just a name · Browse all sites in Careers →

DomainMatchTitleCountry/LangCategoryAI filesContactAI-protection
bsalzberg.com 75 match
1 shared topics
Benjamin Salzberg - Resume United States~ en careers robotsllmsaihumans emailphone none
donhoustonjr.com 70 match
1 shared topics
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brittanyriopelle.com 66 match
1 shared topics
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databaseengineers.com 64 match
1 shared topics
Gregory Hart United States~ en careers robotsllmsaihumans emailphone none
danielreddjones.com 64 match
1 shared topics
Daniel Jones CV en careers robotsllmsaihumans emailphone none
budhirajaankur.com 64 match
1 shared topics
Ankur Budhiraja — Resume en careers robotsllmsaihumans emailphone none
heunghan.com 63 match
1 shared topics
JaeHeung Choi - 최재흥 en careers robotsllmsaihumans emailphone none
srideep.dev 63 match
1 shared topics
Srideep Sunil Kavlekar | Resume en careers robotsllmsaihumans emailphone none
balince.net 63 match
1 shared topics
Portfolio - Josh Balboa en careers robotsllmsaihumans emailphone none
antradzerve.com 62 match
1 shared topics
Antra Dzērve-Štrāla en careers robotsllmsaihumans emailphone none
brianward.co 62 match
1 shared topics
Brian Ward Colombia en careers robotsllmsaihumans emailphone none
reneefromhold.com 62 match
1 shared topics
Renee Fromhold en careers robotsllmsaihumans emailphone none
herwindo.com 62 match
1 shared topics
Resume | Online Resume en careers robotsllmsaihumans emailphone none
danmarquis.com 62 match
1 shared topics
Dan Marquis en careers robotsllmsaihumans emailphone none
keeganhayes.com 62 match
1 shared topics
Keegan Hayes | Product Manager en careers robotsllmsaihumans emailphone none
mdzamantf.com 62 match
1 shared topics
Md. Arifuzzaman en careers robotsllmsaihumans emailphone none
danieljolly.com 61 match
1 shared topics
Daniel Jolly en careers robotsllmsaihumans emailphone none
maykelange.com 61 match
1 shared topics
Hello there! | Maykel’s blog. en careers robotsllmsaihumans emailphone none

How the match score works

Each match is a 0–100 similarity score — the higher it is, the more two sites resemble one another. It’s computed automatically from our own crawl data (never from what a site says about itself) by combining several independent signals, so a high score means several of them point the same way:

No single signal decides the result — they’re blended together. Treat the score as a way to rank candidates rather than an absolute percentage; the chips on each result show which signals contributed.