What Early-Career Tech Job Postings Ask For in 2026: 10,780 Live Listings Counted

Every list of "the most in-demand tech skills" you have read was assembled from survey responses, vendor marketing, or another list. We had a shorter route: count the postings.

This is our own job index — listings pulled from company career pages through Greenhouse, Ashby and Lever, re-verified daily, dead ones retired. On 17 September 2026 it held 10,780 live postings across 1,232 companies.

One thing to know before any number below, because it changes how you read all of them: the board is early-career by construction. A posting is dropped at ingestion if its title carries a senior-level marker — senior, sr., staff, principal, lead, director, VP, head of. That is a product decision (the board exists for people entering the field), and it makes this dataset unusual: almost every published skills ranking blends a principal engineer's job ad with a new grad's. This one cannot, because the principal engineer's ad was never let in.

So: here is what employers wrote down when they were hiring someone early in their career.

Python is named in a third of postings; nothing else is close

Two things in that table are worth arguing with.

Kubernetes (9.9%) outranks JavaScript (6.0%). Infrastructure-as-code is the practice of declaring servers, networks and clusters in version-controlled files rather than configuring them by hand, and it is the cluster Kubernetes and Terraform both belong to. Its tools outrank JavaScript here not because more jobs use them — they plainly do not — but because infrastructure gets named and front-end languages get assumed. A React posting often never writes the word JavaScript. This is what a frequency count measures: what an employer bothered to type.

C++ at 13.3% is higher than almost every published skills ranking puts it. That is our index showing its shape. A deep-tech employer is one whose product depends on hardware or physics rather than only on software — robotics, embedded systems, aerospace, ML infrastructure — and we are heavy in exactly those. A sample of C++ postings on the board on the day we counted included firmware for flight controllers, GNC engineering and ML-infrastructure roles. An index built from large-enterprise listings would show less C++ and more Java.

The AI skills boom is not in the average job ad yet

983 postings — one in eleven — mention LLMs, generative AI or large language models.

The more useful cut is over time. Split the index by when we first saw each posting:

If AI skills were sweeping through hiring the way the discourse suggests, the newer cohort would be the higher one. In our data it is not. We are not claiming demand is falling — a 1.2-point gap across two cohorts is well inside what posting-mix noise can produce — but we can say plainly that we see no surge, and anyone telling a career-changer that every job now requires LLM experience is not describing this data.

Two out of three postings show a salary

Pay transparency is the requirement, now law in several US states, that an employer publish a salary range in the advertisement itself rather than reveal it later in the process. The salary share is steady across cohorts (65.8% for the last 30 days, 64.8% for older postings), which is what you would expect once such rules are in force rather than phasing in. Several US states now require a pay range in the ad, and the US Bureau of Labor Statistics' monthly Employment Situation release is the standard reference for the wider labour-market context these postings sit in.

The remote number is the one that changes behaviour. 17.1% remote means filtering to remote-only removes about five of every six openings on this board. That may still be the right trade for you. It should be a decision, not an accident.

The number we are not publishing

We can count how often a skill is named. We cannot tell you how often it is tested, because we do not see inside the interview. It would be easy to write "Python appears in 34.3% of postings, so a third of your interview will be Python" — and it would be made up.

What we will say, from the questions candidates bring us, is that the gap between named and tested is widest for infrastructure tools and narrowest for the primary language. Treat that as experience, not as data.

Key terms

Frequency count

The share of postings in which a term appears anywhere in the title, summary, skill list, tags or responsibilities. It measures what employers wrote, not what a role requires.

Applicant tracking system (ATS)

The software an employer posts and manages jobs through — Greenhouse, Ashby and Lever in this index. Postings are read from the employer's own ATS-hosted careers page, not from an aggregator.

Live posting

A listing still publicly visible on the employer's careers page on the day we checked. Our index re-verifies daily and retires listings that disappear.

Cohort

A group of postings split by when we first saw them, used here to compare newer listings against older ones without changing the underlying index.

How to use this if you are preparing

1. Rehearse by frequency, not by fear. A skill above 5% will recur across your whole search, so preparation compounds. A skill under 1% deserves an honest paragraph, not a weekend.
2. Prepare one story per named tool in the posting's title. Interviewers ask what you did with a tool, not whether you have heard of it.
3. Say your gaps out loud once before the interview. A rehearsed honest answer costs nothing; an unrehearsed one sounds like a bluff.
4. Check the posting again the day before. Edits to the title or the first responsibility tell you what the hiring manager decided the role actually is.
5. Ask for the band if there isn't one. Two-thirds of postings publish a range, so asking is now the normal case rather than an awkward one.

Method, and what it cannot tell you

Postings are read from employer careers pages through Greenhouse (54.2% of the index), Ashby (28.2%) and Lever (17.6%), then re-verified daily. Every figure above is a count over the 10,780 postings that were live on 17 September 2026.

Four limitations, stated plainly:

1. This is our board, not the job market — and it is early-career only. Postings whose titles carry a senior-level marker (senior, sr., staff, principal, lead, director, VP, head of) are excluded at ingestion, as are non-engineering functions and roles outside US eligibility. It also skews toward startups and scale-ups that publish structured listings. Every figure here therefore describes early-career engineering demand, which is the point, but it is not a market census. The Occupational Outlook Handbook is the place to go for economy-wide occupation data.
2. A term match is not a requirement. We count the word appearing. We cannot tell a hard requirement from a nice-to-have from a copy-pasted boilerplate list.
3. Two counts are deliberate floors. Java excludes anything that could be JavaScript, and Go counts only explicit "Golang" mentions, because "go" is an ordinary English word. Both are lower bounds, published as such rather than inflated with a guess.
4. One day is one day. These are counts from 17 September 2026. We will re-run them rather than quietly leaving a stale number on the page.

Aggregate data available to journalists and researchers on request.

Related guides

• Ghost jobs by the numbers — how long these same postings stay open, from the same index.
• Technical interview questions master guide — what gets asked once the skills on your resume clear the screen.
• CS new-grad interview loop — the round-by-round shape of the loop these postings lead to.
• Mock interview practice for CS new grads — rehearsal before the first phone screen, not after a bad one.

Once a posting is worth your application, the rest is the interview. InterviewChamp.AI is built for that half: rehearse the questions this kind of role actually asks, with your own resume and the real job description in front of you. For a live interview with a person, check what the company allows first. For a test or a take-home, practise beforehand and answer it on your own.