The San Francisco Bay Area is still the largest of the US tech hiring hubs in 2026, with 21,533 distinct technical job openings found in the trailing 90 days, ahead of New York at 18,622 and Washington, DC at 12,156. The more useful finding sits underneath the volume ranking: technical hiring fell 28.3% nationally quarter over quarter, so the hubs worth watching are the ones declining slowest, not the ones posting the biggest raw numbers.
This ranking comes from 265,402 cleaned US technical job openings in PredictLeads proprietary company and job-opening data, measured for the week of September 4, 2026. “Cleaned” is doing real work in that sentence: 44% of the raw candidate pool turned out not to be technology employers at all.
Below are the top 20 hubs by scale and momentum, the five emerging metros clearing our smaller eligibility bar, the nine technical functions driving the numbers, 18 companies whose technical hiring moved sharply in the last quarter, and the methodology, including what it cannot tell you.
TLDR:
- The San Francisco Bay Area leads on volume with 21,533 technical openings in 90 days, followed by New York (18,622) and Washington, DC (12,156). The top six are stable: Bay Area, New York, DC, Austin, Seattle, and Los Angeles appear in the same six slots under every weighting scheme we tested.
- US technical hiring fell 28.3% quarter over quarter, and 14 of the 20 hubs declined less than that baseline. Miami-Fort Lauderdale, New York, and the Bay Area beat the national trend by the widest margins, at 25.1, 21.1, and 13.6 percentage points.
- Company size predicts direction, not just scale. Every size bracket from 11 employees up cut technical hiring, and the cuts got deeper with size, bottoming at -43.2% among 5,001 to 10,000-employee firms. The only two segments still adding openings are single-employee companies (+3.4%) and companies with no size on file yet (+36.6%).
- Nearly half of a naive “tech job postings” pull is not technology employers. Cleaning job boards, IT-staffing firms, and aggregator sites out of 473,958 raw candidate postings left 265,402.
- The analysis runs on the PredictLeads Job Openings dataset: 279.2M+ postings since 2018 across 2.9M+ websites, every record classified with an O*NET occupation code and timestamped with
first_seen_atandlast_seen_at, which is what makes a current-versus-prior-quarter comparison possible per metro.
The top 20 US tech hiring hubs, September 2026
Rank blends five inputs, so a metro can climb on direction rather than size. “Tech Openings” counts distinct technical job postings found in the trailing 90 days after removing job boards, staffing and IT-consulting firms, and aggregator sites posing as employers. “Company Growth” is the change in the number of distinct companies hiring.
| Rank | Tech hub | Tech openings (90d) | Change vs prior 90d | Companies hiring | Company growth |
|---|---|---|---|---|---|
| 1 | San Francisco Bay Area, CA | 21,533 | -14.7% | 4,167 | -6.0% |
| 2 | New York Metro, NY-NJ | 18,622 | -7.2% | 4,316 | -15.8% |
| 3 | Washington, DC Metro | 12,156 | -22.2% | 1,849 | -26.2% |
| 4 | Austin Metro, TX | 4,936 | -23.8% | 1,214 | -16.1% |
| 5 | Seattle Metro, WA | 5,198 | -25.7% | 999 | -17.1% |
| 6 | Los Angeles Metro, CA | 5,350 | -25.5% | 1,443 | -29.4% |
| 7 | Miami-Fort Lauderdale Metro, FL | 1,985 | -3.2% | 1,056 | +29.3% |
| 8 | Dallas-Fort Worth Metro, TX | 6,449 | -26.5% | 1,598 | -26.2% |
| 9 | Denver-Boulder Metro, CO | 3,372 | -24.0% | 1,004 | -24.1% |
| 10 | Boston Metro, MA | 5,236 | -32.0% | 1,294 | -23.5% |
| 11 | Baltimore-Annapolis / Fort Meade Corridor, MD | 3,030 | -27.7% | 475 | -21.6% |
| 12 | Chicago Metro, IL | 4,038 | -30.2% | 1,141 | -31.3% |
| 13 | San Diego Metro, CA | 2,410 | -26.8% | 618 | -25.7% |
| 14 | Pittsburgh Metro, PA | 1,345 | -21.2% | 316 | -22.4% |
| 15 | Detroit Metro, MI | 2,128 | -25.9% | 404 | -27.2% |
| 16 | Columbus Metro, OH | 1,454 | -25.3% | 321 | -23.2% |
| 17 | Houston Metro, TX | 2,720 | -31.7% | 1,012 | -26.9% |
| 18 | Atlanta Metro, GA | 3,597 | -39.7% | 1,053 | -28.0% |
| 19 | Charlotte Metro, NC-SC | 2,201 | -30.4% | 519 | -23.9% |
| 20 | Phoenix Metro, AZ | 2,841 | -38.9% | 878 | -26.9% |
Notice how weakly volume and rank correlate below the top three. Miami ranks 7th on 1,985 openings while Dallas-Fort Worth ranks 8th on 6,449, because Miami declined 3.2% against Dallas-Fort Worth’s 26.5% and added hiring companies while Dallas-Fort Worth lost them. If you are building a territory plan or a market-entry case, that direction column is the one that changes decisions.
Three placements worth a second look
Detroit at 15th is an automotive technical labor market, not a software one. Automotive and mobility companies account for 39.1% of the metro’s technical hiring, with Ford alone at 13.2%. A vendor selling developer tooling into Detroit is selling into vehicle software and manufacturing systems teams, which is a different buying committee entirely. We looked at the same market from the trade-policy angle in our analysis of auto tariffs and automotive hiring.
Pittsburgh (14th) and Columbus (16th) outrank Atlanta and Houston on shallower declines, not on size. Pittsburgh posted 1,345 openings against Atlanta’s 3,597, but fell 21.2% versus Atlanta’s 39.7%. Raleigh-Durham cleared the eligibility bar and still ranked outside the top 20 for the same reason.
The Baltimore-Annapolis / Fort Meade corridor (11th) is a federal and defense-contractor market. Cybersecurity is 17.6% of technical openings there against 5.0% nationally, anchored by Booz Allen and Peraton and by the Fort Meade concentration of NSA and US Cyber Command work. We grouped Baltimore and the Fort Meade corridor together for labor-market coherence, which is an editorial choice rather than a statistical-area identity.
Every figure above is a query against timestamped PredictLeads Job Openings records: 279.2M+ postings since 2018, each carrying location_data, onet_data, first_seen_at, and last_seen_at.
How we ranked the hubs
The score is a weighted blend of five inputs, deliberately tilted so that a mid-size metro changing direction can outrank a large one that is shrinking faster.
- 40% current technical-opening volume. Distinct technical postings found in the trailing 90 days.
- 30% momentum relative to the national trend. The metro’s quarter-over-quarter change measured against the -28.3% national baseline.
- 15% number of distinct companies hiring. Depth of the employer base, not just posting count.
- 10% growth in the number of hiring companies. Whether the employer base is widening or thinning.
- 5% breadth of newly-active employers. How many companies re-entered the market after a quiet stretch.
Momentum is scored against the national trend rather than in absolute terms because the raw quarter-over-quarter window compares a strong spring against a soft summer for every metro at once. Without that adjustment the whole table reads as decline and tells you nothing about relative strength.
Eligibility for the top 20 required at least 700 current-quarter technical openings and at least 100 distinct hiring companies. To confirm the ranking was not an artifact of our weights, we rescored it under four alternative schemes: pure scale, scale-heavy, momentum-heavy, and a 50/50 blend. The same 15 of 20 metros appear in every version, and all four agree on the same top six. The contested slots are the last five.
Role classification uses O*NET-SOC codes rather than title keywords: 33 codes in total, drawn from the Computer and Mathematical occupation family plus three Architecture and Engineering codes covering computer hardware, robotics, and mechatronics engineers. Every PredictLeads job opening carries an O*NET code, which is what makes the same definition of “technical” hold across a 40,000-person bank and a 12-person startup. If you want to reproduce a slice of this yourself, we walk through the mechanics in finding companies hiring for a specific role with O*NET codes.
Where tech hiring is holding up best
Fourteen of the 20 hubs declined less than the national baseline. The chart below plots each metro’s quarter-over-quarter change against that -28.3% baseline, in percentage points. A bar to the right of the line means the metro held up better than the country as a whole; it does not mean the metro grew.
Miami is the standout, and the reason is narrower than a general tech boom. Cloud, infrastructure, and DevOps openings in the Miami-Fort Lauderdale metro rose 212% quarter over quarter, from 198 to 618, while every other technical function in the metro was flat or down. That is an infrastructure story: the buyers moving in that metro are platform and reliability teams, not front-end or analytics teams.
At the other end, Atlanta (-11.4 points) and Phoenix (-10.6 points) are the two large hubs where the slowdown is steepest, and they are the two most likely to be misread. Both still appear in every “fastest growing tech city” list built on office-lease announcements and cost-of-living comparisons. Live posting data says something different this quarter. The same divergence shows up by industry rather than geography in our hiring momentum tracker for the 10 industries accelerating fastest.
One counterweight to all of the above: the most recent month reads better than the quarter containing it. Openings found in the trailing 30 days are up 1.4% against the prior 30 days, and 5.5% above the trailing-90-day monthly average. That is a single month, not a turn, but it is the first positive print in the series.
What companies are hiring for
Nine technical functions account for the bulk of the cleaned national volume, and they did not contract evenly.
| Function | Openings (90d) | Prior 90d | Change |
|---|---|---|---|
| Software Engineering | 53,818 | 70,037 | -23.2% |
| IT / Technical Support | 50,411 | 72,282 | -30.3% |
| Data Engineering / Analytics | 29,279 | 43,248 | -32.3% |
| Cloud / Infrastructure / DevOps | 20,333 | 28,422 | -28.5% |
| Web / UX Development | 15,585 | 24,447 | -36.2% |
| Hardware / Robotics Engineering | 10,969 | 13,921 | -21.2% |
| Cybersecurity | 10,042 | 14,002 | -28.3% |
| QA / Testing | 7,611 | 9,871 | -22.9% |
| AI / Machine Learning (narrow O*NET code) | 3,033 | 4,211 | -28.0% |
Software engineering (-23.2%) and hardware and robotics engineering (-21.2%) held up best. Web and UX development (-36.2%) and data engineering and analytics (-32.3%) were cut hardest. That pattern is consistent with companies protecting core product engineering while trimming the functions they staffed up opportunistically during a growth phase. For a vendor, it also means the accounts most likely to have budget attention right now are the ones posting platform and hardware roles, not the ones posting analytics roles.
The AI hiring picture is geographic, not national
The narrow AI and machine learning occupation code fell 28.0%, in line with everything else, and that figure undercounts AI hiring badly. Most ML and AI engineer postings get classified as ordinary software developer roles, so the occupation code is the wrong lens. Cutting the data by which openings carry an explicit AI or ML reference in the job title gives a very different, and far more concentrated, picture.
AI-titled roles are 5.0% of the Bay Area’s current technical openings, 4.1% of Seattle’s, and 2.2% of Boston’s, against 0.3% in Charlotte and 0.1% in Phoenix. Houston, Detroit, Columbus, and Atlanta are all under 1%. If your product sells to AI and ML teams, the addressable market is effectively three metros plus a long tail, and a national list will waste most of your effort.
New York is the interesting exception in the other direction: its AI-titled openings fell from 451 to 354, down 21.5%, in a quarter when the metro’s overall technical hiring held up better than almost anywhere else. We ran the equivalent analysis across the Atlantic in the AI engineering jobs in Europe hiring report.
Company size predicts direction, not just scale
The single most useful cut in this dataset is not geographic. Segment the same 265,402 openings by the employer’s reported size band and a clean gradient appears: every named bracket from 11 employees up is contracting, and the cuts get deeper as companies get bigger.
[ASSEMBLED FROM SOURCE DATA] Every named bracket from 11 employees up is contracting, and the decline deepens with size, bottoming at -43.2% for firms with 5,001 to 10,000 employees before easing slightly to -36.3% among 10,001-plus employers. The only two segments still adding technical openings are single-employee companies (+3.4%) and the “no size on file” segment (+36.6%), which is overwhelmingly newer, smaller, and stealth-stage companies that have not yet built out a LinkedIn presence.
[ASSEMBLED FROM SOURCE DATA] This single dynamic is the real explanation for the Bay Area and New York’s relative strength above. Broken out by size within each metro, every named bracket from 11 employees up is contracting in both places at rates similar to the rest of the country. Both metros only look resilient because their unsized segment is up 69.3% in the Bay Area (2,714 to 4,595 openings) and 91.7% in New York (2,840 to 5,444 openings), more than offsetting the pullback happening everywhere else in each market. In plain terms, the Bay Area and New York’s outperformance is being carried by a wave of newer companies, not by their large, recognizable employers, which are cutting technical hiring just as hard as companies everywhere else in the country.
Emerging US tech hiring hubs to watch
[ASSEMBLED FROM SOURCE DATA] Five metros below top-20 scale cleared a lower eligibility bar (at least 200 current-quarter openings and 40 hiring companies) while declining materially less than the national baseline, with an identifiable company base behind the numbers rather than a handful of postings.
| Metro | Tech openings (90d) | Companies hiring | vs national trend | What’s driving it |
|---|---|---|---|---|
| St. Louis Metro, MO | 481 | 170 | +16.2% | Software engineering openings up 26.5% (98 to 124), the one bright function in an otherwise typical quarter. |
| Boise, ID | 552 | 144 | +10.1% | A smaller decline than 30 of the 37 qualifying metros we screened. |
| Melbourne, FL | 261 | 66 | +16.8% | Space Coast aerospace and defense corridor; the best company-growth rate of any emerging candidate (-5.7% vs. -15% to -35% elsewhere). |
| Dayton, OH | 393 | 117 | +5.1% | Wright-Patterson AFB-adjacent aerospace and defense tech corridor; web/UX openings up 33% on a small but real base. |
| Columbia, SC | 323 | 96 | +9.9% | Cloud, infrastructure, and DevOps openings up 46.5% (43 to 63), a secondary market absorbing infrastructure work. |
[ASSEMBLED FROM SOURCE DATA] Treat all five as small-base readings rather than a coming wave: Melbourne’s entire technical market is 261 openings across 66 companies, which is one or two accounts changing plans away from being a genuine trend. What they share is a real, named industry driving the number rather than statistical noise from a handful of postings, which is why they clear our bar for “worth watching” even at this scale.
Companies to watch
[ASSEMBLED FROM SOURCE DATA] These are not the largest employers in their metros by volume. They are companies whose technical hiring pattern just changed shape: a sudden surge, a new location, or a jump that coincided with a financing or product signal in PredictLeads’ own hiring-surge detection.
| Company | Location | Openings: prior → current (90d) | Why it’s interesting |
|---|---|---|---|
| Anthropic | New York, NY | 134 → 189 (+41%) | AI research lab scaling NYC technical hiring alongside its SF base. |
| Harvey | New York, NY | 83 → 165 (+99%) | Legal-AI startup; company-wide hiring surge, openings roughly doubled quarter over quarter. |
| Polymarket | New York, NY | 11 → 49 (+345%) | Prediction-market platform; openings up about 4x, paired with a revenue signal. |
| Jerry | New York, NY | 80 → 147 (+84%) | Insurance/auto-ownership app; steady technical hiring surge in NYC. |
| Fluidstack | San Francisco, CA | 42 → 116 (+176%) | AI compute/GPU cloud provider; openings nearly tripled alongside a new-customer signal. |
| Parafin | San Francisco, CA | 12 → 40 (+233%) | Embedded fintech for SMBs; hiring surge paired with a new financing round. |
| MatX | Mountain View, CA | 11 → 40 (+264%) | AI chip (accelerator) startup; company-wide hiring surge. |
| Scale AI | San Francisco, CA | 121 → 45 (-63%) | AI data-labeling infrastructure; large base, recent quarter pulled back after an earlier surge. |
| Varda Space Industries | El Segundo, CA | 24 → 93 (+288%) | In-space manufacturing; hiring surge alongside a new investor signal. |
| Chaos | Hawthorne, CA | 32 → 104 (+225%) | Space/defense systems; openings more than tripled alongside a financing signal. |
| Mach Industries | San Luis Obispo, CA | 26 → 40 (+54%) | Defense-tech (munitions/drones); steady hiring surge. |
| Muon Space | San Jose, CA | 16 → 43 (+169%) | Satellite systems; openings nearly tripled alongside an acquisition signal. |
| CesiumAstro | Westminster, CO | 73 → 91 (+25%) | Space communications hardware; hiring surge alongside acquisition news. |
| Symbotic | Wilmington, MA | 0 → 62 (new) | Warehouse robotics/automation; brand-new hiring surge in the Boston metro. |
| Project44 | Chicago, IL | 16 → 41 (+156%) | Supply-chain visibility SaaS; hiring surge alongside a revenue-increase signal. |
| Mirantis | Austin, TX | 8 → 40 (+400%) | Cloud/Kubernetes infrastructure software; openings quintupled. |
| Form Energy | Weirton, WV | 12 → 40 (+233%) | Long-duration battery manufacturing; hiring surge alongside a product launch. |
| Nscale | New York, NY | 24 → 42 (+75%) | AI-cloud/GPU infrastructure; hiring surge alongside a financing and product-launch signal. |
What this means for sales and GTM teams
[ASSEMBLED FROM SOURCE DATA] Hiring is an observable signal of where a company is putting resources. It is not a guarantee of what it buys next. Treat it as a prompt to look closer, not a trigger to pitch.
| Signal | What it may indicate |
|---|---|
| Rapid engineering hiring | Cloud infrastructure, observability, security, and developer-tooling spend may be about to scale with the new headcount. |
| Rapid AI/data hiring | Compute, data infrastructure, model tooling, governance, and analytics needs may be growing faster than the org chart shows yet. |
| Cybersecurity hiring surge | Often trails a compliance deadline, an incident, or a new security investment cycle, worth confirming which. |
| New geographic engineering hub | Office buildout, payroll and HR systems, local recruiting, and workplace vendors become relevant in that metro specifically. |
| Broad hiring across multiple functions | Often marks a company entering a wider expansion phase rather than backfilling one team. |
| Hiring acceleration with no size profile yet | Frequently a recently founded or stealth-stage company, worth checking for a financing signal before assuming budget exists. |
The hidden signals inside tech hiring data
[ASSEMBLED FROM SOURCE DATA] A city-level ranking is a useful map, but it is a lagging, coarse one. The more useful question sits one level down: which individual companies just changed behavior, a sudden surge, a new office, a department appearing from nothing. Getting there required treating the raw job-posting count with real suspicion first.
[ASSEMBLED FROM SOURCE DATA] Starting from 473,958 raw US technical openings matching occupation and location filters, removing job boards, news, forum, and VC sites, and companies in the IT-staffing and recruiting industries brought that down to 361,343, a 23.8% cut. A second, less obvious pass brought it down further, to 265,402: removing “companies” whose posting volume is statistically implausible for their claimed size. That pass alone removed 201 distinct entities, none claiming more than 200 employees, several on domains like jobcubby.com and bulkhire.app, that were together responsible for over a quarter of the already-cleaned national volume. A company genuinely cannot run more than 150 concurrent, distinct technical requisitions on 200 employees. When the data says one is, it is a site aggregating other people’s jobs, not a hiring company.
[ASSEMBLED FROM SOURCE DATA] That is the real argument for company-level signal over city-level counting. A city’s number is only as clean as every company inside it, and most public “tech jobs by city” figures never make this second cut at all. The ranking above shows where technical investment concentrates geographically. The more durable signal for account research sits one level deeper: which individual companies just started building an AI team, opened a new engineering location, or doubled technical hiring in a quarter.
Methodology
[ASSEMBLED FROM SOURCE DATA] Data and period. PredictLeads proprietary company and job-opening data. “Current” is the trailing 90 days ending with the most recent complete week of data; “previous” is the 90 days before that. A parallel 30-day cut is used for the freshness check in the key findings.
Technical role classification. A job opening counts as technical if PredictLeads’ occupation classifier assigned it an O*NET-SOC code inside the Computer and Mathematical family (SOC 15-1xxx/15-2xxx), excluding actuaries, mathematicians, operations research analysts, statisticians, and general mathematical science occupations, plus three Architecture and Engineering codes for computer hardware, robotics, and mechatronics engineers, 33 codes in total. Sub-functions (software engineering, AI/ML, data, cloud/infrastructure/DevOps, cybersecurity, QA, web/UX, IT support, hardware) are assigned from the same codes, cross-checked against title keywords for the AI/ML cut specifically, since O*NET’s occupation set predates most AI/ML job titles.
Geographic normalization. Locations are the job posting’s own geocoded city and state, not the employer’s headquarters. Cities are grouped into metro hubs following standard Census CBSA membership for well-known hubs (for example, San Jose, Santa Clara, and Sunnyvale into “San Francisco Bay Area”). Ungrouped cities stand alone. Postings with no resolvable city (24% of the clean total) are reported separately, not assigned to a metro; postings whose location string explicitly says “remote” (0.15%) are excluded from every metro figure.
Cleaning and thresholds. Excluded: websites categorized as job boards, news, forums, classifieds, VC firms, or religious sites; companies in the IT-services/IT-consulting or staffing and recruiting industries; companies below a minimum data-quality score; and any company whose posting volume is implausible for its claimed LinkedIn size. Top-20 eligibility requires at least 700 current-quarter openings and at least 100 hiring companies; emerging-hub eligibility uses a lower bar of at least 200 openings and 40 hiring companies. Scoring weights were sensitivity-tested against three alternate schemes (see “How we ranked the hubs” above).
Limitations. Currently-active “stock” figures undercount long-running postings first found more than 180 days ago. AI/ML figures are a title-keyword proxy and will miss AI roles titled generically as “Software Engineer.” Company-size segments reflect LinkedIn’s self-reported ranges, which lag real headcount changes. Metro groupings are a documented editorial choice, not a claim of official Census boundaries in every case (Denver-Boulder and Baltimore-Fort Meade are combined for labor-market coherence, not CBSA identity).
Source: PredictLeads proprietary company and job-opening data, US technical postings, trailing 180 days ending with the most recent complete week.
Frequently Asked Questions
As of the week of September 4, 2026, the top five US tech hiring hubs by blended scale and momentum are the San Francisco Bay Area, the New York metro, Washington DC, Austin, and Seattle. The Bay Area leads on raw volume with 21,533 distinct technical job openings found in the trailing 90 days, ahead of New York at 18,622 and Washington DC at 12,156. The full top 20 also includes Los Angeles, Miami-Fort Lauderdale, Dallas-Fort Worth, Denver-Boulder, Boston, the Baltimore-Fort Meade corridor, Chicago, San Diego, Pittsburgh, Detroit, Columbus, Houston, Atlanta, Charlotte, and Phoenix. The ranking comes from 265,402 cleaned US technical openings in PredictLeads proprietary job-opening data, after removing job boards, staffing firms, and aggregator sites.
The San Francisco Bay Area has the most technical job openings of any US metro, with 21,533 distinct postings found in the trailing 90 days from 4,167 distinct companies. New York is second at 18,622 openings, and it actually has more distinct companies hiring at 4,316. Washington DC is third at 12,156 openings but from only 1,849 companies, which reflects a labor market concentrated in large federal contractors rather than spread across many employers. The company-count difference matters more than the opening count if you are building a target account list rather than sizing a talent market.
No US tech hub grew its technical job openings quarter over quarter in this run, so the honest answer is which hubs declined least. Against a national baseline of -28.3%, Miami-Fort Lauderdale outperformed by 25.1 percentage points at -3.2%, New York by 21.1 points at -7.2%, and the San Francisco Bay Area by 13.6 points at -14.7%. Pittsburgh (+7.1 points) and Washington DC (+6.1 points) round out the top five on momentum. In total, 14 of the 20 hubs declined less than the national baseline, and only Chicago, Charlotte, Houston, Boston, Phoenix, and Atlanta declined faster.
Both are outperforming the national trend, but neither grew. Bay Area technical openings fell 14.7% quarter over quarter and New York’s fell 7.2%, against a national baseline of -28.3%. More importantly, that relative strength is not coming from their large employers: inside both metros, every named size bracket from 11 employees up is contracting at rates similar to the rest of the country. What offsets it is the unsized segment, where openings rose 69.3% in the Bay Area (2,714 to 4,595) and 91.7% in New York (2,840 to 5,444). Both metros are being carried by newer companies, not by recognizable ones.
Five metros too small for the top 20 cleared a lower bar of 200 openings and 40 hiring companies while declining materially less than the national baseline: Melbourne, Florida (+16.8 percentage points), St. Louis (+16.2), Boise (+10.1), Columbia, South Carolina (+9.9), and Dayton, Ohio (+5.1). Three of the five are government-adjacent aerospace and defense markets, including the Space Coast corridor around Melbourne and the Wright-Patterson AFB corridor around Dayton. The clearest single-function story is Columbia, where cloud, infrastructure, and DevOps openings rose 46.5% from 43 to 63. Treat all five as small-base readings: Melbourne’s entire technical market is 261 openings across 66 companies.
Software engineering is the largest technical function at 53,818 US openings in the trailing 90 days, followed by IT and technical support at 50,411, data engineering and analytics at 29,279, and cloud, infrastructure, and DevOps at 20,333. The more useful read is which functions held up: software engineering fell 23.2% and hardware and robotics engineering fell 21.2%, both shallower than the -28.3% national baseline, while web and UX development fell 36.2% and data engineering and analytics fell 32.3%. That pattern is consistent with companies protecting core product engineering while trimming functions staffed up opportunistically during a growth phase. Every PredictLeads job opening carries an O*NET occupation code, which is what makes this comparison consistent across employers of very different sizes.
AI hiring is far more geographically concentrated than technical hiring overall. Openings carrying an explicit AI or machine learning job title are 5.0% of current technical openings in the San Francisco Bay Area, 4.1% in Seattle, and 2.2% in Boston, against 0.3% in Charlotte and 0.1% in Phoenix. Houston, Detroit, Columbus, and Atlanta are all under 1%. Note that the narrow AI and machine learning occupation code is a poor proxy, because most ML and AI engineer postings get classified as ordinary software developer roles, which is why these figures use a title-keyword cut instead. New York is the exception in the other direction: its AI-titled openings fell from 451 to 354, down 21.5%, in a quarter when its overall technical hiring held up better than almost anywhere else.
Large employers cut technical hiring harder than small ones in this run. Openings from companies with 10,001 or more employees fell 36.3%, from 107,425 to 68,439, and the 5,001 to 10,000 bracket fell hardest of all at 43.2%, from 27,740 to 15,755. Every named size bracket from 11 employees up contracted, and the cuts got steeper as company size rose. The only two segments still adding openings are single-employee companies (+3.4%) and companies with no size on file (+36.6%), which is overwhelmingly newer and smaller companies. Size bands here reflect self-reported LinkedIn ranges and lag real headcount changes.
Detroit ranks 15th on 2,128 technical openings across 404 companies, and it is a genuinely automotive-driven technical labor market rather than a software one. Automotive and mobility companies account for 39.1% of the metro’s technical hiring, with Ford alone at 13.2%. Its quarter-over-quarter decline of 25.9% is also shallower than the -28.3% national baseline, which is worth 2.4 percentage points of momentum in the ranking. For a vendor, the practical implication is that Detroit’s technical buyers sit in vehicle software, embedded systems, and manufacturing teams, which is a different buying committee than a SaaS engineering org.
The Baltimore-Annapolis and Fort Meade corridor is the most cybersecurity-concentrated technical labor market in this analysis, with cybersecurity at 17.6% of its technical openings against a 5.0% national average. That is a federal and defense-contractor market anchored by Booz Allen and Peraton and by the Fort Meade concentration of NSA and US Cyber Command work. Nationally, cybersecurity openings fell 28.3% quarter over quarter, from 14,002 to 10,042, exactly in line with the overall baseline. Note that Baltimore and the Fort Meade corridor were grouped together as a documented editorial choice for labor-market coherence, not because they form a single statistical area.
It raises the odds, and it is not proof. Among companies whose quarterly technical openings at least doubled, 15.9% had a financing event in the trailing 18 months, against 7.9% of otherwise-similar companies. That is roughly twice the rate, and it remains a correlation with no direction established: the round may precede the hiring, follow it, or be unrelated. The practical move is to check rather than assume. PredictLeads Financing Events covers 210,800+ events since 2016 with normalized financing types from pre_angel through series_j, so confirming whether a hiring surge sits on top of fresh capital is a single query.
Two passes, and the second one is the one most analyses skip. The first removes job boards, news and forum sites, classifieds, venture-capital sites, and IT-services, staffing, and recruiting companies, which took this dataset from 473,958 raw US technical openings to 361,343, a 23.8% cut. The second removes entities whose posting volume is statistically implausible for their claimed size, which brought it to 265,402. That second pass removed only 201 distinct entities, none claiming more than 200 employees, several on domains like jobcubby.com and bulkhire.app, and those 201 accounted for over a quarter of the already-cleaned national volume. The underlying sanity check is simple: a 200-person company cannot run more than 150 concurrent distinct technical requisitions.
Yes. PredictLeads Job Openings is available by API, flat files, webhooks, and MCP, and postings can be filtered by O*NET occupation code, location, seniority, and date window. The dataset holds 279.2M+ postings since 2018 across 2.9M+ websites, with 10.2M active openings at any time and 710,600+ companies currently hiring. Because every record carries first_seen_at and last_seen_at plus location_data resolved from the posting’s own city rather than employer headquarters, you can rebuild any current-versus-prior-window comparison in this report for your own account list. A free account includes 100 API requests to test the fields on real companies.
Related Guides
- Hiring Momentum Tracker: 10 Industries Accelerating Hiring – the same methodology applied to industries instead of metros.
- How to Find Companies Hiring for a Specific Role with O*NET Codes – how to reproduce a slice of this analysis on your own accounts.
- Best Outbound Buying Signal Tools – where hiring data fits alongside the other signal types.
- Best LinkUp Alternatives for Job Openings Data – how to evaluate job-posting data providers on coverage, history, and delivery.
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