Dasheboard AI — 3 certified H-1B filings (FY2022–FY2023)
- 1
- Filings · FY2023
- $115k
- Median base · FY2023
- Software Engineer
- Top role · 3 all-time
- AZ
- Top state · 3 all-time
Dasheboard AI filed 1 certified H-1B LCAs in FY2023 (down 50% from the year before), with a median base salary of $115k and the middle 50% of offers between $115k and $115k. Across all years it has 3 certified filings since FY2022, most often for Software Engineer in Arizona.
How much does Dasheboard 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. $115k median in FY2023. Base pay only — hover a year for its figures.
How has Dasheboard AI's H-1B hiring changed by year?
2 certified filings in FY2022 → 1 in FY2023. The change column is each year against the one before.
| Fiscal year | Filings | vs prior FY | Median base |
|---|---|---|---|
| FY2023 | 1 | −50% | $115k |
| FY2022 | 2 | — | $95k |
Which wage levels does Dasheboard AI file?
DOL prevailing-wage levels I–IV approximate experience tiers (I = entry, IV = fully competent). 0% of Dasheboard 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 3 filings with a wage level · all years
- Level II100.0%3
What jobs does Dasheboard 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 |
|---|---|---|
| Software Engineer | 3 | $95k |
Where does Dasheboard 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 |
|---|---|---|
| AZ | 3 | $95k |
What has Dasheboard AI filed recently?
Every certified LCA on record for Dasheboard AI: job title, worksite, prevailing-wage level and the offered base salary.
| FY | Job title | Base salary |
|---|---|---|
| 2023 | Software Engineer | $115,000 |
| 2022 | Software Engineer | $95,139 |
| 2022 | Software Engineer | $95,139 |
Common questions about Dasheboard AI's H-1B filings
- How much does Dasheboard AI pay H-1B workers?
- Dasheboard AI's median certified H-1B base salary is $115k (FY2023), from 1 filings. See the full salary distribution and percentiles above.
- How many H-1B workers does Dasheboard AI sponsor?
- Dasheboard AI has 3 certified H-1B Labor Condition Applications on record (FY2022–FY2023).
- What jobs does Dasheboard AI sponsor for H-1B?
- Dasheboard AI's most-sponsored H-1B roles include Software Engineer.
- Where does Dasheboard AI hire H-1B workers?
- Dasheboard AI's top H-1B worksite states are AZ.
- 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 (FY2022–FY2023). An LCA is not an approved visa; pay figures are base salary and exclude bonus and equity. Methodology →