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Large language models (LLMs) jobs in 2026 — demand, top roles hiring, and related skills

As of 2026-09-30, Large language models (LLMs) appears in 2,083 job postings indexed by Skillenai over the past 90 days — Software Engineer has the most postings mentioning Large language models (LLMs), with demand share down 1.4% vs the prior 4 weeks.

Last updated · 90d ending 2026-09-30

Postings · last 90 days
2,083
Demand vs prior month
down 1.4% vs the prior 4 weeks
Top role · 11.3% of skill postings
Software Engineer
Top hiring metro
Bengaluru

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Frequently asked questions about Large language models (LLMs)

+Is Large language models (LLMs) in demand in 2026?

Yes. Large language models (LLMs) appears in 2,083 job postings indexed by Skillenai over the 90 days ending 2026-09-30. Software Engineer accounts for the most postings mentioning Large language models (LLMs) (11.3% of all postings mentioning Large language models (LLMs)).

+What jobs require Large language models (LLMs)?

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 (LLMs) are Generative AI Specialist (93.1% of that role’s postings mention Large language models (LLMs)), AI Data Annotator (90.9% of that role’s postings mention Large language models (LLMs)), AI / ML Engineer (47.1% of that role’s postings mention Large language models (LLMs)).

+What skills are commonly paired with Large language models (LLMs)?

Across job postings indexed by Skillenai (90 days ending 2026-09-30), Large language models (LLMs) most often appears alongside Python, prompt engineering, machine learning, Generative AI, Retrieval-Augmented Generation (RAG).

+Where is Large language models (LLMs) most in demand?

As of 2026-09-30, the metro areas posting the most jobs requiring Large language models (LLMs) are Bengaluru, San Francisco, New York City, London, Toronto, according to the Skillenai jobs index.

+How can I keep up with new Large language models (LLMs) content and jobs?

Skillenai indexes news, blog posts, and research papers mentioning Large language models (LLMs) alongside the jobs index. You can subscribe to a daily email digest of new Large language models (LLMs) content from your Skillenai account.

+Which skills come before and after Large language models (LLMs)?

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 (LLMs) — last 90 days

Salary distribution

Box = 25th–75th percentile · tick = median · whisker = 10th–90th · USD, annualized

Career paths around Large language models (LLMs)

Skills documented before and after this skill across employer changes.

Historical career profiles · all locations

Skills before Large language models (LLMs)

Before Large language models (LLMs)python → Large language models (LLMs): 18 observed employer moves with this skill pairTableau → Large language models (LLMs): 8 observed employer moves with this skill pairsql → Large language models (LLMs): 7 observed employer moves with this skill pairPostgreSQL → Large language models (LLMs): 6 observed employer moves with this skill pairNLP → Large language models (LLMs): 5 observed employer moves with this skill pairdocker → Large language models (LLMs): 5 observed employer moves with this skill pairAWS → Large language models (LLMs): 5 observed employer moves with this skill pairJava → Large language models (LLMs): 5 observed employer moves with this skill pairLargelanguagemodels (LLMs)python: 18 movespython18 movesTableau: 8 movesTableau8 movessql: 7 movessql7 movesPostgreSQL: 6 movesPostgreSQL6 movesNLP: 5 movesNLP5 movesdocker: 5 movesdocker5 movesAWS: 5 movesAWS5 movesJava: 5 movesJava5 moves

Skills after Large language models (LLMs)

After Large language models (LLMs)Large language models (LLMs) → python: 3 observed employer moves with this skill pairLarge language models (LLMs) → machine learning: 2 observed employer moves with this skill pairLarge language models (LLMs) → data integrity: 2 observed employer moves with this skill pairLarge language models (LLMs) → scikit-learn: 2 observed employer moves with this skill pairLarge language models (LLMs) → ETL: 2 observed employer moves with this skill pairLarge language models (LLMs) → Power BI: 2 observed employer moves with this skill pairLarge language models (LLMs) → sql: 2 observed employer moves with this skill pairLarge language models (LLMs) → docker: 2 observed employer moves with this skill pairLargelanguagemodels (LLMs)python: 3 movespython3 movesmachine learning: 2 movesmachine learning2 movesdata integrity: 2 movesdata integrity2 movesscikit-learn: 2 movesscikit-learn2 movesETL: 2 movesETL2 movesPower BI: 2 movesPower BI2 movessql: 2 movessql2 movesdocker: 2 movesdocker2 moves
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.

Observed connections and move counts
ConnectionMoves
Before: python18
Before: Tableau8
Before: sql7
Before: PostgreSQL6
Before: NLP5
Before: docker5
Before: AWS5
Before: Java5
After: python3
After: machine learning2
After: data integrity2
After: scikit-learn2
After: ETL2
After: Power BI2
After: sql2
After: docker2

Roles most likely to require Large language models (LLMs)

Among roles with at least 20 postings in the same period.

RolePostings mentioning skill% of role postings mentioning skill
Generative AI Specialist5493.1%
AI Data Annotator2090.9%
AI / ML Engineer2447.1%
AI Security Specialist1244.4%
Gen AI Engineer420.0%
Generative AI Engineer1018.5%
Frontier Agents Engineer418.2%
Sales Systems Engineer517.9%
Prompt Engineer916.4%
Product Data Scientist1015.9%

Roles with the most Large language models (LLMs) postings

RolePostings mentioning skillShare of skill postings
Software Engineer23511.3%
Data Scientist1567.5%
AI Engineer1527.3%
Machine Learning Engineer954.6%
Product Manager743.6%
Generative AI Specialist542.6%
Forward Deployed Engineer311.5%
ML Engineer291.4%
AI/ML Engineer271.3%
Solutions Architect251.2%

Top companies posting jobs requiring Large language models (LLMs)

Employers ranked by indexed job postings in the last 90 days.

Top companies posting jobs requiring Large language models (LLMs)
CompanyPostings · 90 days
Accenture82
Innodata66
Welo Data47
Google36
Cisco34
Bosch27
CLERA20
PwC19
Snowflake19
NVIDIA16

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 (LLMs)

NamePostingsShare
Bengaluru673.2%
San Francisco542.6%
New York City482.3%
London442.1%
Toronto331.6%
Pune281.3%
Seattle261.2%
Boston251.2%
Hyderabad251.2%

Skills commonly paired with Large language models (LLMs)

Python (1,089)prompt engineering (616)machine learning (582)Generative AI (522)Retrieval-Augmented Generation (RAG) (508)SQL (336)PyTorch (323)AWS (322)LangChain (315)vector databases (306)

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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 (LLMs) 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 (LLMs) postings by all Large language models (LLMs) 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: 1.0% to 1.0%. 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
9dc3c0ab3359bfc0
data_as_of
2026-09-30
window_days
90
Hiring engineers who use Large language models (LLMs)?

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.

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Compiled by Jared Rand · Data sourced from the Skillenai labor market index