large language models jobs in 2026 — demand, top roles hiring, and related skills
As of 2026-09-30, large language models appears in 1,428 job postings indexed by Skillenai over the past 90 days — Software Engineer has the most postings mentioning large language models, with demand share up 5.3% vs the prior 4 weeks.
Last updated · 90d ending 2026-09-30
Which roles want large language models?
Upload your resume and Skillenai will show which roles your large language models experience fits, which skills you already cover, and what is missing.
Prepare to discuss large language models in your interview
We’re building mock interviews informed by job postings and career profiles, to help you explain how you’ve used large language models.
Frequently asked questions about large language models
+Is large language models in demand in 2026?
Yes. large language models appears in 1,428 job postings indexed by Skillenai over the 90 days ending 2026-09-30. Software Engineer accounts for the most postings mentioning large language models (11.8% of all postings mentioning large language models).
+What jobs require large language models?
According to the Skillenai jobs index over the 90 days ending 2026-09-30, among roles with at least 20 postings, the highest shares mentioning large language models are Safeguards Enforcement Analyst (29.6% of that role’s postings mention large language models), AI Response Evaluator (18.5% of that role’s postings mention large language models), AI/ML Scientist (17.4% of that role’s postings mention large language models).
+What skills are commonly paired with large language models?
Across job postings indexed by Skillenai (90 days ending 2026-09-30), large language models most often appears alongside Python, machine learning, Generative AI, SQL, PyTorch.
+Where is large language models most in demand?
As of 2026-09-30, the metro areas posting the most jobs requiring large language models are San Francisco, New York City, London, Toronto, Singapore, according to the Skillenai jobs index.
+How can I keep up with new large language models content and jobs?
Skillenai indexes news, blog posts, and research papers mentioning large language models alongside the jobs index. You can subscribe to a daily email digest of new large language models content from your Skillenai account.
+Which skills come before and after large language models?
The skill-flow chart shows skills documented in adjacent positions across observed employer changes. An outgoing skill is documented in the following position but not the preceding one. These are ideas to explore, not proven prerequisites, acquisition dates, or levels of mastery. Each ribbon counts employer moves with that skill pair; one move can contribute several pairs.
Weekly indexed postings requiring large language models — last 90 days
Salary distribution
Box = 25th–75th percentile · tick = median · whisker = 10th–90th · USD, annualized
Career paths around large language models
Skills documented before and after this skill across employer changes.
Historical career profiles · all locations
Skills before large language models
Skills after large language models
How to read this chart · view counts
Each side is an independent set of observed employer moves, not the same people followed through three stages. Ribbon widths compare move counts within that side. Internal moves are not included.
The following position documents a skill that the preceding position does not. Skills must be linked to both positions, with clear dates and no overlap. One move can connect several skill pairs. These patterns suggest skills to explore; they do not establish prerequisites, when a skill was learned, or a higher skill level.
Source: Skillenai talent graph, historical career profiles. Historical descriptions and coverage can change. Only the leading published connections are shown.
| Connection | Moves |
|---|---|
| Before: python | 14 |
| Before: sql | 5 |
| Before: JavaScript | 5 |
| Before: MYSQL | 4 |
| Before: ETL | 3 |
| Before: Power BI | 3 |
| Before: spark | 2 |
| Before: NLP | 2 |
| After: docker | 3 |
| After: ci/cd | 2 |
| After: sql | 2 |
| After: Microsoft 365 | 2 |
| After: REST APIs | 2 |
| After: Tableau | 2 |
| After: React | 2 |
| After: Power BI | 2 |
Roles most likely to require large language models
Among roles with at least 20 postings in the same period.
| Role | Postings mentioning skill | % of role postings mentioning skill |
|---|---|---|
| Safeguards Enforcement Analyst | 8 | 29.6% |
| AI Response Evaluator | 5 | 18.5% |
| AI/ML Scientist | 4 | 17.4% |
| Prompt Engineer | 9 | 16.4% |
| AI Data Scientist | 3 | 15.0% |
| Application Software Engineer | 8 | 14.5% |
| Applied AI Scientist | 4 | 13.8% |
| Frontier Agents Engineer | 3 | 13.6% |
| AI Research Scientist | 10 | 12.3% |
| Deep Learning Engineer | 4 | 12.1% |
Roles with the most large language models postings
| Role | Postings mentioning skill | Share of skill postings |
|---|---|---|
| Software Engineer | 168 | 11.8% |
| AI Engineer | 95 | 6.7% |
| Data Scientist | 83 | 5.8% |
| Machine Learning Engineer | 80 | 5.6% |
| Product Manager | 43 | 3.0% |
| ML Engineer | 38 | 2.7% |
| Research Scientist | 31 | 2.2% |
| Research Engineer | 22 | 1.5% |
| Applied Scientist | 18 | 1.3% |
| Engineering Manager | 16 | 1.1% |
Top companies posting jobs requiring large language models
Employers ranked by indexed job postings in the last 90 days.
| Company | Postings · 90 days |
|---|---|
| Anthropic | 55 |
| OpenBrain | 48 |
| Cisco | 27 |
| CLERA | 20 |
| Scale AI | 19 |
| SpaceX | 16 |
| Adobe | 15 |
| Gitlab | 14 |
| Elsevier | 12 |
| Xero | 12 |
Job postings indexed over the past 90 days, grouped by resolved employer. Counts are postings, not hires. Companies without a published page appear without a link.
Top metros hiring for large language models
| Name | Postings | Share |
|---|---|---|
| San Francisco | 87 | 6.1% |
| New York City | 74 | 5.2% |
| London | 46 | 3.2% |
| Toronto | 29 | 2.0% |
| Singapore | 28 | 2.0% |
| Bengaluru | 25 | 1.8% |
| San Jose | 23 | 1.6% |
| Washington | 18 | 1.3% |
| Boston | 16 | 1.1% |
Skills commonly paired with large language models
Get a daily email digest of new large language models content
Skillenai indexes news articles, blog posts, and research papers that mention large language models. Click below and we'll open a pre-filled daily digest — change the cadence to hourly or weekly if you prefer, then save. Free account required (~30 seconds).
Explore related pages
How this was computed
Counts derive from the Skillenai jobs index over the 90 days ending 2026-09-30. Skills are resolved against the Skillenai canonical taxonomy, so the same entity is counted whether a posting writes 'Python', 'Python 3', or 'python'. Role prevalence divides postings mentioning large language models by all postings for each role in the same window, ranking roles with at least 20 postings. Role distribution divides each role’s large language models postings by all large language models postings, including postings without a role. Shares need not sum to 100% for the displayed roles. Pages refresh weekly (or daily for the top-50 most-requested skills). Adjusted posting share: 0.6% to 0.6%. Demand share change is the relative percentage change between these adjusted shares. Each employer-and-ATS group has at least 10 postings in each 90-day window; its earlier posting count supplies the same weight in both windows. The panel includes 2,596 identified employers and covers 68% of earlier and 72% of latest indexed postings. Windows: 2026-06-02 to 2026-08-31 and 2026-06-30 to 2026-09-28 (UTC; end dates excluded). The windows overlap by 62 days. Dates reflect indexing, not the employer’s posting date. This measures posting mix, not total hiring or market-wide demand. Matching excludes entrants and exits; changes in crawl completeness within an employer or ATS can still affect the result.
- source
- Skillenai jobs index, deduplicated daily
- entity_id
- 9528acc35deaa202
- data_as_of
- 2026-09-30
- window_days
- 90
The demand, skills, and geo numbers on this page come from the same Skillenai labor market index that powers our API. Use it for compensation benchmarking, hiring-competition analysis, and skill-adoption tracking.
Skillenai for recruiters →