monthly market report
Remote Tech Hiring Report: What the Active Market Shows
This report turns the board's current inventory into a clearly scoped market snapshot: how many roles and companies are active, where listings concentrate, how fresh the supply is, and how much of it includes usable pay information.
live dataset · September 11, 2026
1,839 active roles from 130 companies
571 listings carry a publication date in the last seven days, and 1,231 (67%) include a parseable annual USD band. Category share is shown below.
| Category | Active roles | Share of inventory |
|---|---|---|
| Software Engineering | 677 | 37% |
| Data & AI | 373 | 20% |
| Marketing & Growth | 214 | 12% |
| Product | 157 | 9% |
| DevOps & Infra | 121 | 7% |
| Engineering | 117 | 6% |
| Security | 87 | 5% |
| Design | 71 | 4% |
| Mobile | 16 | 1% |
| QA & Testing | 6 | 0% |
What the snapshot represents
The live panel on this page counts active postings gathered from the public Greenhouse, Lever, and Ashby boards in our company registry. A posting must pass the site's remote-location and technology-role filters, and it must indicate eligibility for the United States, Canada, or both. The result is a focused inventory, not a census of every remote job on the internet.
The unit is an opening, not a company or a person hired. One employer can publish several openings for the same discipline, while another may use one evergreen requisition for several hires. Counts therefore describe advertised opportunity and employer behavior. They should not be converted into estimates of total hiring without additional employer-level evidence.
Read freshness before reading volume
A large catalog can be misleading if most records are old. The live calculation reports how many source records carry a publication date in the previous seven days. We also remove records after a successfully checked source no longer returns them and impose a ninety-day ceiling, which keeps the inventory closer to current demand than an archive of every role ever observed.
Publication dates are supplied by applicant-tracking systems and are not perfectly standardized. An employer may refresh or republish a requisition without changing the underlying team need. Use the new-this-week measure as an activity signal, then inspect the original job page before treating a date as the start of a brand-new search.
Category share is a search-planning tool
Category counts show where this source set has depth. A larger software-engineering share can justify a narrower search by backend, frontend, platform, or language. A smaller design or mobile share calls for broader alerts and quicker review, not the conclusion that the field has disappeared. Supply on one curated board also reflects which employers use supported career systems.
Candidates should compare adjacent categories. A platform engineer may appear under software engineering or DevOps; an applied machine-learning engineer may appear under Data & AI or software engineering. Opening the linked category pages and using title search reduces the cost of imperfect classification.
- Use category totals to decide how narrow an alert can be.
- Use the seven-day count to set a realistic review cadence.
- Use company count to distinguish broad demand from one employer's hiring burst.
- Use salary disclosure as a coverage measure, not a market-pay estimate.
What this report cannot prove
The inventory does not observe applications, interviews, offers, filled seats, layoffs, contractor marketplaces, or roles hosted outside the supported public boards. It cannot establish that remote hiring is rising or falling across the entire economy from one snapshot. A defensible trend requires archived snapshots collected with the same inclusion rules over time.
For external context, the Bureau of Labor Statistics publishes occupation-wide employment and outlook estimates. Those figures cover remote and on-site work together, so they answer a different question. Pairing the broad occupational baseline with this board's current remote openings is useful; treating them as the same dataset is not.
A practical monthly routine
Record the total, seven-day additions, company count, leading categories, and salary-disclosure rate on the same day each month. Add notes for source changes or major employer hiring bursts. After several periods, compare directions rather than overinterpreting small point changes.
For an individual search, turn the report into a weekly allocation: spend more time on fresh roles in deep categories, keep broader alerts for thin categories, and revisit companies with multiple relevant openings. The aim is not to predict the labor market; it is to spend application time where observable supply exists.
Sources and further reading
continue with live listings
Browse relevant remote jobs
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