Refolk
September 12, 2026·9 min read

No US Tech Hub Grew Last Quarter. Miami Declined 1/9th as Fast.

PredictLeads' Sept 4, 2026 report shows US tech hiring fell 28.3% QoQ. Miami beat the baseline by 25 points. Here's the sourcing map that follows.

tech hiring hubs 2026where are tech companies hiringtech job postings by citysourcing candidates MiamiUS technical hiring momentum
No US Tech Hub Grew Last Quarter. Miami Declined 1/9th as Fast.

If your Q4 territory plan is ranked by 90-day opening volume, you are running last quarter's map. PredictLeads' September 4, 2026 US tech hiring hubs report shows the national baseline fell 28.3% quarter over quarter, and Miami-Fort Lauderdale outperformed that baseline by 25.1 points. The volume leaders and the momentum leaders are no longer the same cities.

The headline: technical hiring fell 28.3% QoQ, and no US hub grew

Every one of the top 20 US tech hubs shrank quarter over quarter in PredictLeads' September 4, 2026 report. The interesting question is not which metros grew (none did) but which declined least, because that is where the reachable, still-warm hiring managers actually sit.

Fourteen of the 20 tracked hubs declined less than the national -28.3% baseline. Six declined faster: Chicago, Charlotte, Houston, Boston, Phoenix, and Atlanta. Those six are your deprioritize list this quarter. The mechanism is straightforward: layoffs and hiring freezes hit the largest employers hardest in absolute terms, which compresses the top of the volume list while leaving mid-sized and satellite metros with steadier flow.

28.3%
Quarter-over-quarter drop in US technical job openings
PredictLeads' September 4, 2026 tech hiring hubs report. No tracked hub grew; Miami declined least.

The correct framing for a sourcer is momentum against the baseline, not raw openings. A metro at -3% is roughly nine times healthier than one at -28%, even if the -28% metro has more absolute reqs, because the -3% metro is where reqs are still moving through committee.

Miami beat the Bay by 25 points. Here is the full leaderboard

Miami-Fort Lauderdale declined 3.2% quarter over quarter, which is 25.1 points better than the -28.3% national baseline and roughly one-ninth the national rate of decline. New York came in second on momentum at -7.2%, followed by the San Francisco Bay Area at -14.7%.

Metro90-day openingsQoQ changeDelta vs baseline
San Francisco Bay Area21,533-14.7%+13.6 pts
New York18,622-7.2%+21.1 pts
Washington DC12,156-22.2%+6.1 pts
Miami-Fort Lauderdalenot disclosed-3.2%+25.1 pts
Pittsburghnot disclosed-21.2%+7.1 pts
US baseline--28.3%0

Two takeaways in the numbers. First, the top six on volume (Bay Area, NY, DC, Austin, Seattle, LA) are stable across every weighting scheme PredictLeads tested, so they belong in every territory. Second, momentum shuffles the order. If you weight by momentum, Miami and Pittsburgh jump into the top five, and Boston and Atlanta drop off entirely.

A metro at minus three percent is nine times healthier than one at minus twenty-eight, no matter which has more open reqs.

Why Pittsburgh and DC keep getting under-ranked

Pittsburgh (+7.1 points) and Washington DC (+6.1 points) close out the top five on momentum, and both are chronically under-weighted in vendor-supplied city rankings. The reason is a data hygiene problem covered in the next section: raw employer pools inherit LinkedIn industry tags without cleaning, which inflates metros that host lots of nominal tech companies (agencies, MSPs, IT resellers) and understates metros where the tech employer base is smaller but more concentrated in actual product companies and federal contractors.

The 44% junk rate: why your "tech company" list lies

A large share of the raw candidate employer pool in most sourcing lists is not a tech employer at all once cleaned. That methodological gap is why volume-ranked city lists keep pointing sourcers at the wrong metros, and it compounds with the sector-level distortion PredictLeads flagged separately: Professional, Scientific and Technical Services (the broad NAICS bucket containing software, IT services, consultancies, and engineering practices) posted the second-sharpest month-over-month decline of the 20 sectors measured, down 3.2%, which hides real divergence between sub-industries.

Here is the mechanism. Most sourcing platforms and data vendors accept LinkedIn's or a similar third party's industry tag at face value. A company self-selects "Information Technology and Services" and gets counted, whether it is a 12-person Salesforce reseller in Tampa or a frontier lab. When a large slice of your universe is agencies, staffing firms, MSPs, and consultancies, three things break:

  1. City rankings over-weight metros that host lots of small IT services shops
  2. Company counts inflate, so headline "there are 8,000 tech companies here" claims survive no scrutiny
  3. Boolean searches against the pool return candidates whose current employer is technically an IT company but not a product engineering environment

This is the exact gap Refolk closes for sourcers who want a cleaned universe: describe the kind of employer you actually want ("US product companies with in-house engineering, exclude agencies, resellers, and MSPs") in plain English, and Refolk applies that filter across GitHub, LinkedIn, and the open web before it ranks anyone.

What "Miami tech" actually means in 2026

Miami tech is now mostly Big Tech satellite offices, not the 2021-era crypto and VC narrative. In Refolk's index of professional profiles, the top current employers of Miami-area software engineers are Google, Meta, Microsoft, and IBM, with a long tail of finance-adjacent tech and a smaller startup base than the headlines suggest.

That matters for outbound in three specific ways:

  • Passive candidates concentrate in a small number of large logos. If you are running Miami outbound, the first six companies in your target list should cover the majority of your reachable pool.
  • Local startup pools are thinner than headline capital numbers suggest. Miami-Fort Lauderdale startups raised $832 million across 100 deals in Q2 2026, and nearly $2 billion over Q1 and Q2 combined, but most of that headcount is still ramping.
  • The metro added roughly 35,000 net tech jobs between 2020 and 2025, behind only Austin among fast-growers, so the momentum is not built on a hollow base. Refolk's index of roughly 349,000 US "Software Engineer" profiles surfaces Miami-Fort Lauderdale alongside SF and Austin as a top current-region cluster even in small random samples. It is dense enough now to run keyword-agnostic queries against.

Nameable Miami employers for a target list

If you are building a Miami target list this week, these are defensible entries beyond the Big Tech satellites:

  • Securitize. The $1.25 billion SPAC deal made tokenization a headline story and the company a real engineering employer in Miami.
  • Analytic Partners. Relocated HQ to Miami in 2019, before the hub reputation existed; useful early-mover benchmark.
  • The LegalTech Fund (Fort Lauderdale, $110M Fund II) and Ascenta Capital (West Palm, $325M) as anchor LPs behind a portfolio of South Florida engineering hires.
  • CI Financial at 830 Brickell as a cautionary example: promised-versus-actual hiring in the relocation wave has diverged, so verify current headcount before you build a raid list.

For the local beat, Refresh Miami and Nancy Dahlberg remain the credible journalistic source. Cite them when you need to justify a Miami expansion to a partner who still thinks the city is a crypto punchline.

Where to run outbound this quarter, by metro

Rank your Q4 outbound territories by momentum first, and break ties on cleaned pool size rather than 90-day openings. Below is the ranking that falls out of the September 4 data.

Tier 1 (run outbound aggressively):

  1. Miami-Fort Lauderdale (-3.2%). Reachable pool concentrated inside six or seven large employers.
  2. New York (-7.2%). Deep pool at 18,622 openings, fintech and AI both hiring.
  3. Pittsburgh (-21.2%). Under-ranked because vendor lists over-weight tech-services metros; concentrated pool at CMU-adjacent product companies.

Tier 2 (keep, but temper expectations):

  1. San Francisco Bay Area (-14.7%). Still the largest absolute pool at 21,533 openings, but reqs move slowly and competition per candidate is highest. For scale context, California still holds an estimated 1.46 million tech workers in 2025, and in San Jose tech is roughly 27% of total employment, so the base is not going anywhere.
  2. Washington DC (-22.2%, 12,156 openings). Federal contractor demand is holding; clearances matter more than momentum.
  3. Austin, Seattle, LA. Stable top-six volume; case-by-case on momentum.

Tier 3 (deprioritize):

  1. Chicago, Charlotte, Houston, Boston, Phoenix, Atlanta. All declined faster than the -28.3% baseline. Keep warm accounts, do not open new territories.

The sourcer's playbook: momentum plus a cleaned pool

The two-step playbook for this quarter is: rank metros by momentum against the -28.3% baseline, then run outbound against a cleaned employer universe. Everything else is noise.

Concretely, that means three changes to how most teams work right now:

  1. Stop building territory plans off 90-day opening counts. Volume rewards the metros that got hit hardest.
  2. Filter the employer universe before you filter people. If your candidate pool is contaminated with agencies, resellers, and MSPs, no amount of Boolean cleverness on the person side will fix the shortlist.
  3. Weight the metros where reqs are still moving. A -3.2% Miami req has a materially higher chance of closing this quarter than a -28% Boston req, because the hiring manager, the recruiter, and the budget are all still active.

Refolk is built for exactly this workflow: describe the metro, the momentum signal, the cleaned employer type, and the seniority in plain English, and get back a ranked shortlist with current employer, tenure, and a public signal that explains the ranking.

FAQ

Which US metros should I prioritize for tech sourcing in Q4 2026?

Miami-Fort Lauderdale, New York, and Pittsburgh lead on momentum against PredictLeads' -28.3% national baseline, at -3.2%, -7.2%, and -21.2% respectively. Keep the Bay Area, DC, Austin, Seattle, and LA in your rotation for volume, and deprioritize Chicago, Charlotte, Houston, Boston, Phoenix, and Atlanta, all of which declined faster than the national baseline. Ranking territories by momentum rather than 90-day opening volume is the single biggest change most teams should make this quarter.

Is Miami actually a real tech hub or still hype?

Miami is a real hub now, but not the one the 2021 headlines described. Refolk's index shows the top current employers of Miami-area software engineers are Google, Meta, Microsoft, and IBM, meaning most technical talent sits inside Big Tech satellite offices rather than local startups. The metro added roughly 35,000 net tech jobs from 2020 to 2025 (behind only Austin) and startups raised nearly $2 billion in the first half of 2026, so the base is real; it just concentrates in a smaller number of large logos than the funding numbers suggest.

Why do "tech company" lists mislead city rankings?

Because a large share of the raw employer pool most vendors sell as "tech companies" turns out to be agencies, IT services firms, MSPs, or consultancies once cleaned. That contamination inflates city rankings toward metros hosting lots of small services shops and pollutes Boolean searches with candidates whose current employer is nominally tech but not a product engineering environment. Cleaning the employer universe before you rank people is the fastest way to improve reply rates without changing your messaging.

Should I still source in the Bay Area?

Yes, but with tempered expectations and a shorter list of target employers. The Bay Area still leads on absolute volume at 21,533 90-day openings, but its -14.7% QoQ decline puts it third on momentum, behind Miami and New York. Treat it as a stable Tier 2 territory: keep your existing accounts warm, expect longer time-to-close, and route net-new outbound capacity toward the Tier 1 metros where reqs are actually moving.

Try it on the search you came here for

Stop building boolean strings. Just describe the person.

Type one sentence. I plan the search, read GitHub, public LinkedIn and Crunchbase records, and the open web as it is right now, and hand back a ranked list with the reason next to every name.

  1. 01Describe them

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  2. 02I read the web live

    GitHub, public LinkedIn and Crunchbase records, the open web. Not a database that went stale last quarter.

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