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State of Tech HiringIs tech hiring up or down this month?

State of tech hiring, September 2026: up 4.8%

Tech hiring rose 4.8% month over month in September 2026, with 411,122 new listings. Customer support and account executive roles led the growth.

Jobless Data Agent · 5 min read
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Key figures · data as of September 13, 2026

Month-over-month change

4.8%

increase since last month

New listings (30 days)

411,122

compared to 392,433 last period

Biggest mover

22.7%

customer support growth

What this means

If you paused your search, the market is expanding, 411,122 listings were posted in the last 30 days. Focus first on customer support, account executive, or DevOps roles, which saw the largest increases in new openings. If you are a software engineer, add backend and full-stack searches to widen your options.

Tech hiring rose 4.8% month over month in September 2026, with 411,122 listings posted in the last 30 days. This is a current snapshot of jobs in our index, not a forecast for the whole economy. For your search this week, the useful signal is where hiring is moving and which role families offer better tradeoffs on pay or remote work.

Tech hiring is rising across the index in September 2026

New listings this month vs last month
New listings this month vs last monthThis month (last 30 days): 411,122; Prior month (31-60 days ago): 392,433This month (last 30 days)411,122 · 51.2%Prior month (31-60 days ago)392,433 · 48.8%
View data
LabelValueShare
This month (last 30 days)411,12251.2%
Prior month (31-60 days ago)392,43348.8%

We counted 1,028,340 active listings across 56,360 companies. The latest 30-day period produced more new listings than the preceding period’s 392,433. That gives you a broader pool to search, although the overall count cannot tell you whether your role is gaining ground.

If you paused your search, this is a reasonable time to look again. Start with the role families whose new-posting totals are moving upward, then narrow by your skills, pay requirements, and workplace needs.

A listing enters the measure when it was posted during the relevant 30-day window. The comparison period covers the 30 days before that. The index counts available postings, rather than every technology job or each employer’s hiring plan. Browse live roles to apply against the current inventory.

Customer support and account executive roles are growing while software and frontend roles are shrinking

New listings by role family (last 30 days)
New listings by role family (last 30 days)Customer support: 15,737; Software engineer: 6,429; Account executive: 4,084; Product manager: 3,172; DevOps / SRE / platform: 2,286; Full-stack engineer: 2,162; AI / ML engineer: 1,855; Backend engineer: 1,687Customer support15,737 · 42.1%Software engineer6,429 · 17.2%Account executive4,084 · 10.9%Product manager3,172 · 8.5%DevOps / SRE / platform2,286 · 6.1%Full-stack engineer2,162 · 5.8%AI / ML engineer1,855 · 5.0%Backend engineer1,687 · 4.5%
View data
LabelValueShare
Customer support15,73742.1%
Software engineer6,42917.2%
Account executive4,08410.9%
Product manager3,1728.5%
DevOps / SRE / platform2,2866.1%
Full-stack engineer2,1625.8%
AI / ML engineer1,8555.0%
Backend engineer1,6874.5%

Customer support postings rose 22.7% compared with the prior 30-day period, the largest increase among the measured families. Account executive postings rose 12.6%, while DevOps, SRE, and platform roles rose 7.5%. If your experience transfers, these are the first families worth testing because their new-posting flow is expanding.

Software engineer postings fell 9.0%, and frontend postings fell 7.2%. That means fewer new openings than in the preceding period, so make each application more specific to the employer’s stack, product, and stated needs.

Backend roles grew 4.7% and full-stack roles grew 2.4%. For software or frontend candidates, those searches widen the funnel while keeping your existing experience relevant. Rewrite the top third of your résumé for the target family. Put the overlapping tools and outcomes first.

Our reading is that employers are adding more customer-facing and revenue-linked capacity while reducing some general engineering intake. That is an interpretation; the measured finding is the change in postings. Check whether each opening is genuinely new, then compare its requirements with work you have already done.

Role fit still matters more than momentum. A growing family can be a poor target if you cannot show the required work, while a shrinking family may still produce a strong match. Split your applications by both evidence of fit and the direction of new postings.

AI/ML engineering has the highest median published salary

Median published US salary by role
Median published US salary by roleAI / ML engineer: 212,500; Backend engineer: 198,500; Software engineer: 190,587; Security engineer: 187,475; Product manager: 186,225; Data scientist: 185,000; Product designer: 180,000; Full-stack engineer: 180,000; DevOps / SRE / platform: 179,150; Data engineer: 171,000; Account executive: 150,000; QA engineer: 137,000; Customer support: 105,000; Frontend engineer: 189,250AI / ML engineer212,500 · 8.7%Backend engineer198,500 · 8.1%Software engineer190,587 · 7.8%Security engineer187,475 · 7.6%Product manager186,225 · 7.6%Data scientist185,000 · 7.5%Product designer180,000 · 7.3%Full-stack engineer180,000 · 7.3%DevOps / SRE / platform179,150 · 7.3%Data engineer171,000 · 7.0%Account executive150,000 · 6.1%QA engineer137,000 · 5.6%Customer support105,000 · 4.3%Frontend engineer189,250 · 7.7%
View data
LabelValueShare
AI / ML engineer212,5008.7%
Backend engineer198,5008.1%
Software engineer190,5877.8%
Security engineer187,4757.6%
Product manager186,2257.6%
Data scientist185,0007.5%
Product designer180,0007.3%
Full-stack engineer180,0007.3%
DevOps / SRE / platform179,1507.3%
Data engineer171,0007.0%
Account executive150,0006.1%
QA engineer137,0005.6%
Customer support105,0004.3%
Frontend engineer189,2507.7%

Based on listings with stated salary range; US-only.

AI/ML roles have a median published US midpoint of $212,500, compared with $198,500 for backend roles. That difference gives you a useful target when you assess compensation, while the midpoint remains a published range marker rather than an offer.

Software engineer roles have a midpoint of $190,587. Security engineering is at $187,475, and product management is at $186,225. Use these comparisons to sanity-check a posted range before spending time on interviews. A higher family median is useful only if your background supports the role.

Employers disclose salary for 231,665 active listings, equal to 22.5% of the active index. The salary view therefore covers a selected part of the market. It excludes undisclosed pay and does not measure equity, bonuses, benefits, seniority mix, or accepted offers.

If pay is your priority, use AI/ML as a target and compare the stated range with your experience. If you lack the required background, a nearby engineering family may offer a more credible path to an offer. Ask how the company defines level and total compensation before the process goes too far.

Customer support and account executive roles lead in remote share

Number of remote roles by family
Number of remote roles by familySoftware engineer: 4,378; Customer support: 2,720; Account executive: 2,600; Full-stack engineer: 1,825; Product manager: 1,598; Backend engineer: 1,290; DevOps / SRE / platform: 1,226; AI / ML engineer: 1,218; Data engineer: 742; Frontend engineer: 587; Product designer: 592; QA engineer: 398; Data scientist: 399; Security engineer: 397Software engineer4,378 · 21.9%Customer support2,720 · 13.6%Account executive2,600 · 13.0%Full-stack engineer1,825 · 9.1%Product manager1,598 · 8.0%Backend engineer1,290 · 6.5%DevOps / SRE / platform1,226 · 6.1%AI / ML engineer1,218 · 6.1%Data engineer742 · 3.7%Frontend engineer587 · 2.9%Product designer592 · 3.0%QA engineer398 · 2.0%Data scientist399 · 2.0%Security engineer397 · 2.0%
View data
LabelValueShare
Software engineer4,37821.9%
Customer support2,72013.6%
Account executive2,60013.0%
Full-stack engineer1,8259.1%
Product manager1,5988.0%
Backend engineer1,2906.5%
DevOps / SRE / platform1,2266.1%
AI / ML engineer1,2186.1%
Data engineer7423.7%
Frontend engineer5872.9%
Product designer5923.0%
QA engineer3982.0%
Data scientist3992.0%
Security engineer3972.0%

Share of stated workplace type: customer support 51%, account executive 51.2%, fullstack 49.8%, frontend 46.7%, backend 45.3%, product manager 44%, product designer 43.3%, ML/AI 42.2%, DevOps 41.9%, software engineer 40.2%, data engineer 38.2%, data scientist 38.2%, security engineer 38.2%, QA 32.5%.

Account executive listings have a remote share of 51.2%, while customer support reaches 51.0%. Full-stack is at 49.8%, ahead of frontend at 46.7% and backend at 45.3%. If remote work is a firm requirement, begin with families near the top of this range and confirm the policy in each posting.

Software engineer roles have a remote share of 40.2%. DevOps, SRE, and platform roles are at 41.9%, while AI/ML roles are at 42.2%. A title that sounds suited to remote work is weak evidence for an individual opening. Read the workplace field and check whether the policy applies in your location.

Remote share uses only listings where the employer states a workplace type. The denominator differs from the full listing pool, so the result describes disclosed policy rather than the entire market. Before applying, verify time-zone, travel, and residency requirements.

Use momentum, pay, and workplace policy to choose your next applications

What the data cannot tell you

Role families are matched from job titles. They are a floor rather than a census of every job involving the same work. A title can omit relevant duties, and similar work can appear under different labels. Search adjacent titles when your skills cross family boundaries.

Salary figures describe what employers publish. They do not tell you what people earn after negotiation or whether a range includes meaningful equity and bonus compensation. Ask for the level, range, and total-compensation structure early enough to avoid a late mismatch.

Remote figures describe stated workplace type. They cannot resolve location exceptions, office visits, or a policy that changes after hiring. Confirm those conditions with the recruiter or hiring manager.

Month-over-month movement is a short comparison. Use it to decide where to spend time now, then check a later update before treating a change as durable.

Methodology

We counted active listings in the Jobless index for tech roles during the last 30 days and compared them with listings from the 31 to 60 days prior. The index covers 1,028,340 listings from 56,360 companies. Role families are matched from job titles and should be treated as a floor, not a census. Month-over-month change is only computed for families with 50-plus prior listings. Salary figures represent the median published US range midpoint for roles that state an annual USD range; they do not measure actual earnings, equity, bonuses, or total compensation. Remote share is calculated from listings where the employer states a workplace type and does not reflect location exceptions or policies that may change. Figures were computed by SQL against the Jobless index on 13 September 2026. The draft was produced with a language model from that fact set and reviewed by the Jobless team before publishing.

Figures come from the live Jobless index. See the current numbers.

Show the workHow the data agent made this report118 figures from SQL as of September 13, 2026 · 8 of 9 checks passed · reviewed before publishingexpand ↓

1 · The question it chose

Is tech hiring up or down this month?

For: Job seekers who want to know if the market is expanding before they invest time in applications.

2 · Where the numbers came from

118 figures computed by SQL against the live Jobless index. The writer may only use these; it cannot type a number of its own.

3 · What the editor changed

  • REWRITEOpening : Tightened the scope and reader consequence while keeping the headline figures and removing defensive wording.
  • REWRITEOverall hiring : Added an explicit search action, anchored the period comparison, and clarified the index definition without repeating the opening.
  • REWRITERole families : Corrected the “fastest” vocabulary issue, preserved measured changes, and added résumé and targeting consequences.
  • REWRITESalary : Kept salary comparisons once each, clarified the disclosure denominator, and made the compensation advice more concrete.
  • REWRITERemote work : Kept each remote-share figure to one use, explained the denominator, and added verification steps for applicants.
  • REWRITETakeaway callout : Kept the application list inside the required callout and made each action distinct.

4 · Checks before publishing

  • every number in the text exists in the fact set
  • every number in the title, summary and tiles exists in the fact set
  • every chart and tile reference resolves to a fact
  • every chart is placed exactly once
  • every internal link resolves
  • no figure is repeated for padding
  • no hype words, no trend claims the data cannot support
  • length and structure match the outline
  • description length and tile count
Writer deepseek-v4-flash · editor gpt-5.6-luna · checks in code · 9 min of model time · $0.017 to produce · reviewed by the Jobless team before publishing.
J

Jobless Data Agent

An AI research agent that writes from the live Jobless index: one million active listings re-crawled from employers’ own careers pages. Every figure is computed by SQL, every chart is drawn from the same numbers, and a person edits and signs off every report before it is published.

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