agentic workflows jobs in 2026 — demand, top roles hiring, and related skills
As of 2026-11-05, agentic workflows appears in 2,442 job postings indexed by Skillenai over the past 90 days — Software Engineer has the most postings mentioning agentic workflows, with demand share up 1.1% vs the prior 4 weeks.
Last updated · 90d ending 2026-11-05
Which roles want agentic workflows?
Upload your resume and Skillenai will show which roles your agentic workflows experience fits, which skills you already cover, and what is missing.
Frequently asked questions about agentic workflows
+Is agentic workflows in demand in 2026?
Yes. agentic workflows appears in 2,442 job postings indexed by Skillenai over the 90 days ending 2026-11-05. Software Engineer accounts for the most postings mentioning agentic workflows (15.8% of all postings mentioning agentic workflows).
+What jobs require agentic workflows?
According to the Skillenai jobs index over the 90 days ending 2026-11-05, among roles with at least 20 postings, the highest shares mentioning agentic workflows are Forward Deployed AI Engineer (29.8% of that role’s postings mention agentic workflows), AI Platform Architect (20.8% of that role’s postings mention agentic workflows), Gen AI Engineer (20.0% of that role’s postings mention agentic workflows).
+What skills are commonly paired with agentic workflows?
Across job postings indexed by Skillenai (90 days ending 2026-11-05), agentic workflows most often appears alongside Python, prompt engineering, CI/CD, LLMs, AWS.
+Where is agentic workflows most in demand?
As of 2026-11-05, the metro areas posting the most jobs requiring agentic workflows are New York City, San Francisco, London, Bengaluru, Singapore, according to the Skillenai jobs index.
+How can I keep up with new agentic workflows content and jobs?
Skillenai indexes news, blog posts, and research papers mentioning agentic workflows alongside the jobs index. You can subscribe to a daily email digest of new agentic workflows content from your Skillenai account.
+Which skills come before and after agentic workflows?
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 agentic workflows — last 90 days
Salary distribution
Box = 25th–75th percentile · tick = median · whisker = 10th–90th · USD, annualized
Career paths around agentic workflows
Skills documented before and after this skill across employer changes.
Historical career profiles · all locations
Skills before agentic workflows
Skills after agentic workflows
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: TailwindCSS | 1 |
| Before: Go-to-market readiness | 1 |
| Before: SaaS integrations | 1 |
| Before: deep learning pipelines | 1 |
| Before: MYSQL | 1 |
| Before: assessment results | 1 |
| Before: interactive dashboards | 1 |
| Before: Power BI | 1 |
| After: python | 1 |
| After: RAG pipelines | 1 |
| After: aws sagemaker | 1 |
| After: data pipelines | 1 |
| After: tensorflow | 1 |
| After: deep learning models | 1 |
| After: pytorch | 1 |
Roles most likely to require agentic workflows
Among roles with at least 20 postings in the same period.
| Role | Postings mentioning skill | % of role postings mentioning skill |
|---|---|---|
| Forward Deployed AI Engineer | 31 | 29.8% |
| AI Platform Architect | 5 | 20.8% |
| Gen AI Engineer | 4 | 20.0% |
| Data Science Lead | 4 | 17.4% |
| Product Program Manager | 4 | 16.7% |
| Founding Product Engineer | 4 | 15.4% |
| AI Operations Specialist | 3 | 15.0% |
| AI Operations Engineer | 6 | 14.3% |
| AI Solutions Engineer | 3 | 14.3% |
| Design Program Manager | 3 | 13.0% |
Roles with the most agentic workflows postings
| Role | Postings mentioning skill | Share of skill postings |
|---|---|---|
| Software Engineer | 387 | 15.8% |
| Product Manager | 211 | 8.6% |
| AI Engineer | 197 | 8.1% |
| Data Scientist | 72 | 2.9% |
| Engineering Manager | 63 | 2.6% |
| Forward Deployed Engineer | 59 | 2.4% |
| Security Engineer | 43 | 1.8% |
| Applied AI Engineer | 38 | 1.6% |
| Machine Learning Engineer | 35 | 1.4% |
| Solutions Architect | 35 | 1.4% |
Top companies posting jobs requiring agentic workflows
Employers ranked by indexed job postings in the last 90 days.
| Company | Postings · 90 days |
|---|---|
| Cisco | 53 |
| NVIDIA | 36 |
| ServiceNow | 27 |
| Elsevier | 24 |
| Palo Alto Networks | 24 |
| Highmetric | 22 |
| Procore | 21 |
| CLERA | 20 |
| Mistral | 17 |
| 16 |
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 agentic workflows
| Name | Postings | Share |
|---|---|---|
| New York City | 112 | 4.6% |
| San Francisco | 89 | 3.6% |
| London | 64 | 2.6% |
| Bengaluru | 48 | 2.0% |
| Singapore | 34 | 1.4% |
| Toronto | 33 | 1.4% |
| Santa Clara | 29 | 1.2% |
| San Jose | 28 | 1.1% |
| Tel Aviv | 27 | 1.1% |
Skills commonly paired with agentic workflows
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 2026-11-05. 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 agentic workflows by all postings for each role in the same window, ranking roles with at least 20 postings. Role distribution divides each role’s agentic workflows postings by all agentic workflows 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 2,472 identified employers and covers 71% of earlier and 70% of latest indexed postings. Windows: 2026-07-07 to 2026-10-05 and 2026-08-04 to 2026-11-02 (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
- b3d468ac5dfddfb3
- data_as_of
- 2026-11-05
- window_days
- 90