LLMOps jobs in 2026 — demand, top roles hiring, and related skills
As of 2026-09-30, LLMOps appears in 557 job postings indexed by Skillenai over the past 90 days — AI Engineer has the most postings mentioning LLMOps, with demand share down 0.8% vs the prior 4 weeks.
Last updated · 90d ending 2026-09-30
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Frequently asked questions about LLMOps
+Is LLMOps in demand in 2026?
Yes. LLMOps appears in 557 job postings indexed by Skillenai over the 90 days ending 2026-09-30. AI Engineer accounts for the most postings mentioning LLMOps (21.9% of all postings mentioning LLMOps).
+What jobs require LLMOps?
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 LLMOps are AI/ML Architect (15.4% of that role’s postings mention LLMOps), AI Enablement Lead (10.7% of that role’s postings mention LLMOps), AI Data Scientist (10.0% of that role’s postings mention LLMOps).
+What skills are commonly paired with LLMOps?
Across job postings indexed by Skillenai (90 days ending 2026-09-30), LLMOps most often appears alongside MLOps, Python, CI/CD, RAG, observability.
+Where is LLMOps most in demand?
As of 2026-09-30, the metro areas posting the most jobs requiring LLMOps are Bengaluru, London, Puteaux, Singapore, San Francisco, according to the Skillenai jobs index.
+How can I keep up with new LLMOps content and jobs?
Skillenai indexes news, blog posts, and research papers mentioning LLMOps alongside the jobs index. You can subscribe to a daily email digest of new LLMOps content from your Skillenai account.
+Which skills come before and after LLMOps?
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 LLMOps — last 90 days
Salary distribution
Box = 25th–75th percentile · tick = median · whisker = 10th–90th · USD, annualized
Career paths around LLMOps
Skills documented before and after this skill across employer changes.
Historical career profiles · all locations
Skills before LLMOps
Skills after LLMOps
No published outgoing skill pairs yet.
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: Explainable AI | 1 |
| Before: NLP | 1 |
| Before: pipeline monitoring | 1 |
| Before: ci/cd | 1 |
| Before: ETL | 1 |
| Before: Azure OpenAI | 1 |
| Before: real-time data pipeline | 1 |
| Before: RAG pipelines | 1 |
Roles most likely to require LLMOps
Among roles with at least 20 postings in the same period.
| Role | Postings mentioning skill | % of role postings mentioning skill |
|---|---|---|
| AI/ML Architect | 4 | 15.4% |
| AI Enablement Lead | 3 | 10.7% |
| AI Data Scientist | 2 | 10.0% |
| Forward Deployed AI Engineer | 9 | 9.5% |
| Developer Relations Engineer | 3 | 9.4% |
| AI Engineering Director | 4 | 7.5% |
| Applied Value Engineer | 3 | 7.5% |
| GenAI Engineer | 3 | 7.3% |
| AI Architect | 20 | 7.0% |
| AI Analyst | 2 | 6.9% |
Roles with the most LLMOps postings
| Role | Postings mentioning skill | Share of skill postings |
|---|---|---|
| AI Engineer | 122 | 21.9% |
| Software Engineer | 26 | 4.7% |
| AI Architect | 20 | 3.6% |
| Data Scientist | 19 | 3.4% |
| Machine Learning Engineer | 19 | 3.4% |
| ML Engineer | 17 | 3.1% |
| AI/ML Engineer | 14 | 2.5% |
| AI Platform Engineer | 13 | 2.3% |
| Forward Deployed AI Engineer | 9 | 1.6% |
| AI/ML Engineering Manager | 8 | 1.4% |
Top companies posting jobs requiring LLMOps
Employers ranked by indexed job postings in the last 90 days.
| Company | Postings · 90 days |
|---|---|
| Wavestone | 18 |
| Accenture | 16 |
| Devoteam | 14 |
| Cloudera | 13 |
| Workato | 12 |
| Databricks | 11 |
| Verta | 11 |
| Caylent | 11 |
| Reuters | 11 |
| Bosch | 11 |
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 LLMOps
| Name | Postings | Share |
|---|---|---|
| Bengaluru | 23 | 4.1% |
| London | 17 | 3.1% |
| Puteaux | 13 | 2.3% |
| Singapore | 12 | 2.2% |
| San Francisco | 9 | 1.6% |
| Hyderabad | 8 | 1.4% |
| Madrid | 7 | 1.3% |
| Charlotte | 6 | 1.1% |
| Cork | 6 | 1.1% |
Skills commonly paired with LLMOps
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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 LLMOps by all postings for each role in the same window, ranking roles with at least 20 postings. Role distribution divides each role’s LLMOps postings by all LLMOps 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: 0.3% to 0.3%. 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
- ecbe4a39be921031
- 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.
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