Job Boards That Use Government Labor Data to Verify Visa Sponsorship History

A job posting that reads "visa sponsorship available" carries no guarantee behind it. The employer attaching those words to a listing may never have filed a single LCA or H-1B petition with any government agency in its history. That gap between the claim and the filing record is where international candidates lose the resource that matters most in an immigration-linked job search: time on the visa clock.

LinkedIn offers no filter tied to actual filing history. A candidate has to search "visa sponsorship" as a keyword and sort through a results page that mixes real sponsors with employers who copied the phrase into a template without ever intending to follow through. Many posts on Indeed carry the same unfiled claim, so a candidate who applies without checking is operating on a guess. Meanwhile, the employers with genuine, years-long filing histories often look identical, on the page, to the ones bluffing. The signal that would separate them already exists in public government records. That signal never appears on the listing itself, and the rest of this piece works through that failure.

How the two government data sources work

Two public government sources, the DOL's Foreign Labor Application Gateway (FLAG) system and the USCIS H-1B Employer Data Hub, give distinct views of an employer's sponsorship activity, and conflating them overstates certainty. They measure different things, and treating them as interchangeable overstates what either one can confirm.

The Labor Condition Application, or LCA, is the form an employer files with the Department of Labor before submitting most H-1B petitions. Each LCA certifies a wage level and working conditions for one specific position, and the DOL publishes disclosure data listing every employer that filed for H-1B, H-1B1, and E-3 roles, down to job titles, wages, and locations. The most recent full quarter, FY2026 Q3, covers activity through June 30, 2026, and spans LCA, permanent labor certification, and prevailing wage records totaling more than 830,000 certified positions.

An LCA shows some things clearly and leaves others unconfirmed:

| LCA data proves | LCA data does not prove | |---|---| | The employer sought DOL certification tied to H-1B, H-1B1, or E-3 employment | That USCIS approved an H-1B petition | | Job title, worksite city and state, attested wage level, and certification dates | That any specific worker obtained H-1B status |

The USCIS H-1B Employer Data Hub answers the question LCA data cannot. It's the official government source for petition-level outcomes: approval rates, denial rates, and petition volumes for both initial and continuing employment, running from fiscal year 2009 to the present. Where an LCA records intent, the Hub records what actually happened, which makes it the only primary source for whether a sponsorship attempt succeeded. As of August 2026, the USCIS Hub contains employer-level data through FY2026 Quarter 3, and the DOL and USCIS datasets do not cover identical periods, so comparing them requires care.

LCA data tells a candidate an employer filed intent to sponsor, and USCIS petition data tells them whether that intent turned into an approval. A platform built on LCA data alone can only speak to the first half of that sentence, and treating it as proof of the second half overstates what it has actually confirmed.

Green card sponsorship runs on a separate track worth a brief mention. PERM labor certification data shows that DOL certified a permanent labor certification tied to a specific role, but it doesn't confirm that Form I-140 was approved or that a Green Card was ever issued.

How job boards turn filings into a signal

None of this government data is proprietary. What a job board actually sells is the labor of matching those records to a live listing, so a candidate sees the filing history at the moment they find the job, not three browser tabs later.

That translation happens in roughly three shapes. The first builds sponsorship verification directly into the listings themselves, cross-checking every posted job against the underlying LCA record before a candidate ever clicks apply. The second layers verification onto listings a candidate has already found somewhere else, adding a confirmation step to a job search the platform didn't originate. FrogHire.ai works this way: its sponsorship signals attach to listings users find through other channels, confirming an employer's filing history rather than generating the discovery on its own.

The third shape skips job listings altogether and functions purely as a reference layer. The USCIS H-1B Employer Data Hub is the anchor, searchable by employer name, city, state, ZIP code, or NAICS code, and H1BData.info indexes over 4.8 million LCA records from DOL disclosure data, filterable by job title, employer, work location, and salary range. These tools are useful for building a target list of employers with real filing histories. What they cannot do is tell a candidate whether that employer has an opening today that matches their role. A reference database alone still leaves half the job search undone.

What each major platform does with the data

No platform currently closes the full loop from verified filing history to live openings to confirmed petition outcomes in one place. Each makes a different tradeoff, and the value of knowing that tradeoff is that a candidate can stack tools intelligently instead of trusting any single one to do everything.

H1BVisaJobs.com cross-checks every listing against real LCA filings rather than self-reported claims, and it goes beyond confirming a company sponsors to showing how they sponsor: total filings, approval rate, and wage-level distribution per employer, across a dedicated set of H-1B sponsor profiles and green-card-sponsorship profiles.

FrogHire.ai occupies a dual role. It checks sponsorship history on listings a candidate finds elsewhere, and it also runs its own daily-updated H1B job list pulled from LinkedIn, Indeed, Glassdoor, Handshake, and Google Jobs, making it both a verification overlay and an independent discovery source depending on how a candidate uses it.

For pure reference work, the USCIS H-1B Employer Data Hub remains the only truly primary source in the category, covering approvals and denials for both initial and continuing employment from fiscal year 2009 to the present. H1BData.info serves a complementary purpose, with its 4.8 million-plus LCA records filterable by job title, employer, location, and salary, useful for wage benchmarking once a candidate has a shortlist of employers to check.

General boards sit at the other end of the spectrum. LinkedIn has no sponsorship filter tied to filing history at all: a candidate has to search "visa sponsorship" as a keyword and then run every promising employer through a separate OFLC lookup before applying. Indeed shares the same structural gap, with many sponsorship claims carrying no LCA filing behind them, which makes the platform's real strength, its sheer volume of postings, only useful once paired with outside verification.

One government-run board serves a narrower purpose. SeasonalJobs.dol.gov covers H-2A agricultural and H-2B seasonal non-agricultural roles, and every posting there is tied to an actual temporary labor certification rather than a self-reported claim, making it the authoritative source for those two visa classes specifically.

Across every platform in this category, one limitation holds. A filing from three years ago does not prove an employer's sponsorship policy today, and no database currently tracks whether a company's current hiring practice still matches its historical filing pattern.

Why filing volume alone misleads

The employer with the most LCA filings on record isn't automatically the best target for any given candidate. Occupational fit, wage level, and approval-rate patterns tell a more useful story than a raw count of petitions filed.

DOL's FY2026 Q3 data shows why volume alone can mislead. Grandison Management, Inc. led all employers in certified LCA positions through June 30, 2026, with Qualcomm Technologies, Amazon.com Services LLC, CGI Technologies & Solutions, Cisco Systems, several Goldman Sachs entities, Apple, and Meta Platforms also appearing prominently in the same dataset. A single familiar brand like Goldman Sachs can file under multiple legal entities. Goldman Sachs shows up as several distinct entries in the FY2026 Q3 table, so employer research has to happen at the entity level, since checking the brand name alone can miss most of its actual filing volume.

Occupation skews the numbers too. Software developers made up a substantial share of all certified FY2026 LCA positions through Q3, so aggregate volume rankings lean heavily toward that single occupation. A candidate in any other field who reads a volume ranking without filtering by occupation is comparing their prospects against a chart built mostly for someone else's job title.

Wage-level distribution offers a sharper filter than volume ever will. The wage-level distribution within an employer's LCA history adds a practical filter: H1BVisaJobs.com's breakdown of wage distributions per employer shows whether a company sponsors primarily entry-level or senior roles, directly relevant to where a candidate should focus energy. Approval rate matters just as much as either of those. An employer with a high denial rate or an erratic filing pattern signals a riskier bet regardless of how many total petitions it has filed, and the USCIS Hub's approval and denial figures are the check that a large LCA volume alone cannot provide.

IT services firms sponsor more total visas and often hire entry-level candidates more readily, while direct tech employers like Google, Microsoft, and Meta pay substantially higher salaries. Neither option is the better one in the abstract. The right answer depends on whether a candidate is optimizing for a foothold or for a paycheck, and the filing data supports either strategy once read at that level of detail. Cap-exempt employers add a third path: universities, their affiliated nonprofits, nonprofit research organizations, and government research organizations can file at any point in the year and skip the H-1B lottery entirely. For a candidate whose biggest obstacle is lottery timing rather than qualifications, that structural exemption is worth more than a spot at the top of any filing-volume list.

How 2026 rule changes weaken historical filing data

Three changes taking effect in 2026 are reshaping what a filing history can actually predict about future sponsorship, and they weaken, in specific and measurable ways, the core premise that past filings forecast future behavior.

The first is the wage-weighted lottery introduced for the FY 2027 registration cycle, effective February 27, 2026, and applied during that March's registration window. Higher-wage registrations now draw better odds, and entry-level odds have fallen accordingly. That shift turns wage level in an employer's historical LCA record into a lottery-viability signal, not just a wage-compliance detail: a company with a pattern of filing at Level I wages now points to weaker lottery outcomes going forward, even if that same company's overall approval rate has historically looked strong. A candidate reading last year's approval rate without checking this year's wage-level pattern is reading half the picture.

A DOL proposed rule on prevailing wages, published in March 2026, would significantly raise the required prevailing wage and make sponsorship more expensive. A rule like that doesn't just make future filings more expensive. It changes the incentive structure that produced the historical filing pattern candidates are reading in the first place, which means an employer's past behavior stops being a clean predictor of its future behavior once the underlying cost of that behavior changes.

None of this makes historical filing data useless. It makes it a snapshot rather than a forecast. A candidate who reads it that way understands the record, while one who reads it otherwise has simply memorized it. Platforms that filter listings by verified filing history, rather than by self-reported claims, still give candidates the clearest starting point available. Migrate Mate is one platform that takes this approach, filtering job listings by verified sponsorship history so a candidate can see, before applying, whether an employer has actually filed petitions for roles resembling their own. That kind of filtering doesn't erase the uncertainty introduced by a shifting lottery formula or a pending wage rule. It just means a candidate spends their applications on employers with a real, checkable record instead of a template phrase copied onto a job posting.