Causify AI — 2 certified H-1B filings (FY2025–FY2026)
- 1
- Filings · FY2025
- $111k
- Median base · FY2025
- AI Engineer
- Top role · 1 all-time
- GA
- Top state · 1 all-time
Causify AI filed 1 certified H-1B LCAs in FY2025, with a median base salary of $111k and the middle 50% of offers between $111k and $111k. That is 8% below the market median for the same job titles. Across all years it has 2 certified filings since FY2025, most often for AI Engineer in Georgia.
How much does Causify AI pay H-1B workers?
Certified base salary by fiscal year: each box is the p25–p75 range, the heavy line the median, the whiskers reach p10–p90. $111k median in FY2025. Base pay only — hover a year for its figures.
How has Causify AI's H-1B hiring changed by year?
1 certified filings in FY2025 → 1 in FY2026. The change column is each year against the one before.
| Fiscal year | Filings | vs prior FY | Median base |
|---|---|---|---|
| FY2026 | 1 | 0% | $105k |
| FY2025 | 1 | — | $111k |
Which wage levels does Causify AI file?
DOL prevailing-wage levels I–IV approximate experience tiers (I = entry, IV = fully competent). 0% of Causify AI's filings sit at Level III–IV. A heavy I–II skew reads as entry-level or contractor-style hiring; a heavy IV skew as senior in-house roles — and higher levels earn more lottery entries.
Share of 2 filings with a wage level · all years
- Level I50.0%1
- Level II50.0%1
What jobs does Causify AI sponsor for H-1B?
The most-filed job titles across all years (DOL titles, employer pay-grade codes stripped), with base-salary percentiles.
| Job title | Filings | Median base |
|---|---|---|
| AI Engineer | 1 | $111k |
| Data Scientist | 1 | $105k |
Where does Causify AI hire H-1B workers?
Worksite states on the certified filings, all years. Deeper pink = more filings; hover a state for its figures.
| State | Filings | Median base |
|---|---|---|
| GA | 1 | $105k |
| MD | 1 | $111k |
What has Causify AI filed recently?
Every certified LCA on record for Causify AI: job title, worksite, prevailing-wage level and the offered base salary.
| FY | Job title | Base salary |
|---|---|---|
| 2026 | Data Scientist | $105,000 |
| 2025 | AI Engineer | $110,739 |
Common questions about Causify AI's H-1B filings
- How much does Causify AI pay H-1B workers?
- Causify AI's median certified H-1B base salary is $111k (FY2025), from 1 filings. See the full salary distribution and percentiles above.
- How many H-1B workers does Causify AI sponsor?
- Causify AI has 2 certified H-1B Labor Condition Applications on record (FY2025–FY2026).
- What jobs does Causify AI sponsor for H-1B?
- Causify AI's most-sponsored H-1B roles include AI Engineer, Data Scientist.
- Where does Causify AI hire H-1B workers?
- Causify AI's top H-1B worksite states are GA, MD.
- Does a certified LCA mean an H-1B visa was approved?
- No. A Labor Condition Application (LCA) is the Department of Labor attestation an employer must have certified before filing an H-1B petition with USCIS. It records the job, worksite and offered wage, but not whether the petition was filed, selected in the lottery, or approved. Filing counts measure intent to sponsor, not headcount.
- What salary do these figures show?
- The base annual wage offered on the certified LCA, converted to a yearly amount. Bonus, equity, overtime and benefits are not included, so total compensation is typically higher. Figures are medians and percentiles over certified filings; wages above $5,000,000 a year are excluded as data-entry errors.
- What do prevailing-wage levels I–IV mean?
- The Department of Labor assigns each LCA an OES wage level from I (entry) to IV (fully competent) for the occupation and area. Under the FY2027 wage-weighted H-1B lottery rule, a higher level earns more selection entries, so an employer's level mix is a proxy for how senior its sponsored roles are.
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Source: U.S. Department of Labor, Office of Foreign Labor Certification — certified LCA disclosure data through June 2026 (FY2025–FY2026). An LCA is not an approved visa; pay figures are base salary and exclude bonus and equity. Methodology →