Semantic Kernel jobs in 2026 — demand, top roles hiring, and related skills
As of 2026-10-29, Semantic Kernel appears in 445 job postings indexed by Skillenai over the past 90 days — AI Engineer has the most postings mentioning Semantic Kernel, with demand share up 13.7% vs the prior 4 weeks.
Last updated · 90d ending 2026-10-29
Which roles want Semantic Kernel?
Upload your resume and Skillenai will show which roles your Semantic Kernel experience fits, which skills you already cover, and what is missing.
Frequently asked questions about Semantic Kernel
+Is Semantic Kernel in demand in 2026?
Yes. Semantic Kernel appears in 445 job postings indexed by Skillenai over the 90 days ending 2026-10-29. AI Engineer accounts for the most postings mentioning Semantic Kernel (27.0% of all postings mentioning Semantic Kernel).
+What jobs require Semantic Kernel?
According to the Skillenai jobs index over the 90 days ending 2026-10-29, among roles with at least 20 postings, the highest shares mentioning Semantic Kernel are AI Technical Lead (14.8% of that role’s postings mention Semantic Kernel), Agentic AI Engineer (10.7% of that role’s postings mention Semantic Kernel), AI Agent Engineer (10.5% of that role’s postings mention Semantic Kernel).
+What skills are commonly paired with Semantic Kernel?
Across job postings indexed by Skillenai (90 days ending 2026-10-29), Semantic Kernel most often appears alongside LangChain, Python, LangGraph, AutoGen, prompt engineering.
+Where is Semantic Kernel most in demand?
As of 2026-10-29, the metro areas posting the most jobs requiring Semantic Kernel are Bengaluru, Singapore, Hyderabad, London, Pune, according to the Skillenai jobs index.
+How can I keep up with new Semantic Kernel content and jobs?
Skillenai indexes news, blog posts, and research papers mentioning Semantic Kernel alongside the jobs index. You can subscribe to a daily email digest of new Semantic Kernel content from your Skillenai account.
+Which skills come before and after Semantic Kernel?
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 Semantic Kernel — last 90 days
Career paths around Semantic Kernel
Skills documented before and after this skill across employer changes.
Historical career profiles · all locations
Skills before Semantic Kernel
Skills after Semantic Kernel
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: Azure | 2 |
| Before: scikit-learn | 1 |
| Before: Azure DevOps | 1 |
| Before: ServiceNow | 1 |
| Before: python | 1 |
| Before: hugging face | 1 |
| Before: SciPy | 1 |
| Before: langgraph | 1 |
| After: python | 1 |
| After: langgraph | 1 |
| After: Strands Agents SDK | 1 |
| After: AgentCore | 1 |
| After: FastAPI | 1 |
| After: AWS Samples | 1 |
| After: langchain | 1 |
| After: Azure OpenAI GPT-4o | 1 |
Roles most likely to require Semantic Kernel
Among roles with at least 20 postings in the same period.
| Role | Postings mentioning skill | % of role postings mentioning skill |
|---|---|---|
| AI Technical Lead | 4 | 14.8% |
| Agentic AI Engineer | 6 | 10.7% |
| AI Agent Engineer | 8 | 10.5% |
| AI Systems Architect | 2 | 9.1% |
| GenAI Engineer | 3 | 8.6% |
| AI Solution Engineer | 2 | 6.5% |
| Forward Deployed Software Engineer | 3 | 6.0% |
| Generative AI Engineer | 3 | 6.0% |
| AI Engineering Lead | 2 | 5.6% |
| AI Platform Architect | 1 | 5.0% |
Roles with the most Semantic Kernel postings
| Role | Postings mentioning skill | Share of skill postings |
|---|---|---|
| AI Engineer | 120 | 27.0% |
| Software Engineer | 31 | 7.0% |
| Data Scientist | 17 | 3.8% |
| AI Architect | 14 | 3.1% |
| AI Software Engineer | 11 | 2.5% |
| Security Engineer | 10 | 2.2% |
| Forward Deployed Engineer | 9 | 2.0% |
| Forward Deployed Solution Engineer | 9 | 2.0% |
| AI Agent Engineer | 8 | 1.8% |
| Agentic AI Engineer | 6 | 1.3% |
Top companies posting jobs requiring Semantic Kernel
Employers ranked by indexed job postings in the last 90 days.
| Company | Postings · 90 days |
|---|---|
| ServiceNow | 12 |
| Kyndryl | 11 |
| PwC | 11 |
| Accenture | 11 |
| Bosch | 10 |
| JCI | 8 |
| Encora | 7 |
| Cisco | 7 |
| Procore | 5 |
| Visa | 5 |
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 Semantic Kernel
| Name | Postings | Share |
|---|---|---|
| Bengaluru | 18 | 4.0% |
| Singapore | 11 | 2.5% |
| Hyderabad | 10 | 2.2% |
| London | 9 | 2.0% |
| Pune | 8 | 1.8% |
| San Jose | 7 | 1.6% |
| Bucharest | 5 | 1.1% |
| New York City | 5 | 1.1% |
| Chí Linh | 4 | 0.9% |
Skills commonly paired with Semantic Kernel
Explore related pages
How this was computed
Weekly job-count charts omit the incomplete current week (weeks start Monday, UTC). Totals include all postings in the stated window. Counts derive from the Skillenai jobs index over the 90 days ending 2026-10-29. 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 Semantic Kernel by all postings for each role in the same window, ranking roles with at least 20 postings. Role distribution divides each role’s Semantic Kernel postings by all Semantic Kernel 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: 0.1% to 0.2%. 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 2,482 identified employers and covers 71% of earlier and 70% of latest indexed postings. Windows: 2026-06-30 to 2026-09-28 and 2026-07-28 to 2026-10-26 (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
- 620df73f2e2d95e5
- data_as_of
- 2026-10-29
- window_days
- 90