Expensify, Inc.

Professional, Scientific & Technical Services · Primarily CA · PERM filings 2020–2024

#13,465 top sponsor

Overview

Expensify, Inc. is a Professional, Scientific & Technical Services employer that has filed 5 PERM green-card applications between FY2020 and FY2024. That places it #13,465 among all U.S. PERM sponsors in our dataset. 5 were certified (100% approval rate), taking about 358 days on average. The most-sponsored role is Software Developers, with most worksites in CA, and the median sponsored wage is $200,000.

5

PERM filings

100%

approval

0

denied

$200,000

median wage

358d

avg processing

Worker background

Across 3 filings with beneficiary data, the most common country of origin is INDIA (33%). (From legacy PERM form data, FY2020–FY2024.)

Top countries of origin

  • India1
  • Spain1
  • Australia1

Prior visa status

  • H-1B2
  • E-31

Education

  • Master's2
  • Bachelor's1

PERM filings by year

Occupations & job titles

The occupations Expensify, Inc. most often sponsors, with average wages.

OccupationFilingsAvg wage
Software Developers 1 $215,000
Software Developers, Applications 1 $200,000
Human Resources Manager 1 $150,000
Training and Development Managers 1 $150,000

Common job titles

Software Engineer(s) 2 Software Engineer 1 Human Resources Lead 1 Program Development Manager and Trainer(s) 1

Worksite states

Wage range

$150,000

25th

$200,000

median

$215,000

75th

$250,000

90th

Law firms used

  • Minami Tamaki LLP4
  • Minami Tamaki, LLP1

Recent filings

CaseJob titleStatusWorksiteDecision
G-100-24163-093882 Software Engineer(s)Certified San Francisco, CA Sep 9, 2025
G-100-23192-178815 Software Engineer(s)Certified - Expired New York, NY Sep 16, 2024
A-23138-44637 Program Development Manager and Trainer(s)Certified - Expired New York, NY May 30, 2024
A-22180-81213 Human Resources LeadCertified - Expired San Francisco, CA Jul 26, 2023
A-20299-13087 Software EngineerCertified - Expired San Francisco, CA Jun 1, 2021

Source: U.S. DOL OFLC PERM disclosure data. Wages are annual-equivalent; outliers excluded.