structured outputs jobs in 2026 — demand, top roles hiring, and related skills
As of 2026-09-30, structured outputs appears in 500 job postings indexed by Skillenai over the past 90 days — AI Engineer has the most postings mentioning structured outputs, with demand share up 3.1% vs the prior 4 weeks.
Last updated · 90d ending 2026-09-30
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Frequently asked questions about structured outputs
+Is structured outputs in demand in 2026?
Yes. structured outputs appears in 500 job postings indexed by Skillenai over the 90 days ending 2026-09-30. AI Engineer accounts for the most postings mentioning structured outputs (16.4% of all postings mentioning structured outputs).
+What jobs require structured outputs?
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 structured outputs are AI Engineering Lead (20.6% of that role’s postings mention structured outputs), Forward Deployed AI Engineer (15.8% of that role’s postings mention structured outputs), Application Software Engineer (14.5% of that role’s postings mention structured outputs).
+What skills are commonly paired with structured outputs?
Across job postings indexed by Skillenai (90 days ending 2026-09-30), structured outputs most often appears alongside Python, prompt engineering, TypeScript, tool use, RAG.
+Where is structured outputs most in demand?
As of 2026-09-30, the metro areas posting the most jobs requiring structured outputs are San Francisco, New York City, Bengaluru, London, San Jose, according to the Skillenai jobs index.
+How can I keep up with new structured outputs content and jobs?
Skillenai indexes news, blog posts, and research papers mentioning structured outputs alongside the jobs index. You can subscribe to a daily email digest of new structured outputs content from your Skillenai account.
+Which skills come before and after structured outputs?
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 structured outputs — last 90 days
Salary distribution
Box = 25th–75th percentile · tick = median · whisker = 10th–90th · USD, annualized
Career paths around structured outputs
Skills documented before and after this skill across employer changes.
Not enough linked career history to draw this chart yet.
Roles most likely to require structured outputs
Among roles with at least 20 postings in the same period.
| Role | Postings mentioning skill | % of role postings mentioning skill |
|---|---|---|
| AI Engineering Lead | 7 | 20.6% |
| Forward Deployed AI Engineer | 15 | 15.8% |
| Application Software Engineer | 8 | 14.5% |
| AI Product Engineer | 10 | 12.2% |
| Agent Engineer | 2 | 9.5% |
| AI Platform Architect | 2 | 9.1% |
| AI Engineering Manager | 8 | 9.0% |
| AI Deployment Engineer | 4 | 8.2% |
| Agentic AI Engineer | 5 | 8.1% |
| AI Systems Engineer | 3 | 6.7% |
Roles with the most structured outputs postings
| Role | Postings mentioning skill | Share of skill postings |
|---|---|---|
| AI Engineer | 82 | 16.4% |
| Software Engineer | 78 | 15.6% |
| Applied AI Engineer | 25 | 5.0% |
| Forward Deployed AI Engineer | 15 | 3.0% |
| Machine Learning Engineer | 14 | 2.8% |
| Data Scientist | 12 | 2.4% |
| LLM Application Engineer | 12 | 2.4% |
| AI Platform Engineer | 10 | 2.0% |
| AI Product Engineer | 10 | 2.0% |
| AI Engineering Manager | 8 | 1.6% |
Top companies posting jobs requiring structured outputs
Employers ranked by indexed job postings in the last 90 days.
| Company | Postings · 90 days |
|---|---|
| Highmetric | 31 |
| Blend360 | 16 |
| ServiceNow | 16 |
| Bjakcareer | 12 |
| Commercetools | 9 |
| Traba | 8 |
| SpaceX | 8 |
| Drata | 7 |
| UiPath | 6 |
| Tekion | 6 |
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 structured outputs
| Name | Postings | Share |
|---|---|---|
| San Francisco | 32 | 6.4% |
| New York City | 24 | 4.8% |
| Bengaluru | 23 | 4.6% |
| London | 10 | 2.0% |
| San Jose | 10 | 2.0% |
| Santa Clara | 10 | 2.0% |
| Berlin | 8 | 1.6% |
| Singapore | 7 | 1.4% |
| Bucharest | 6 | 1.2% |
Skills commonly paired with structured outputs
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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 structured outputs by all postings for each role in the same window, ranking roles with at least 20 postings. Role distribution divides each role’s structured outputs postings by all structured outputs 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: 0.2% 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 2,595 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
- ed461e376a3569b9
- 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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