State of AI Careers 2026
The overall shape of the AI job market: role distribution, skill demand, remote share and salary disclosure, from tracked job postings.
Generated Sep 29, 2026 · Dataset window: Dec 5, 2009 – Sep 29, 2026 · Observations: 3,302
Executive summary
Analysis of 3,302 active AI job postings from 15 companies, collected from public employer career pages and ATS systems. AI Agent Engineering and Forward Deployed roles are the fastest-moving new categories in the tracked dataset.
Role distribution
The tracked market splits across 12+ canonical roles. The table below shows the largest role categories by active job count.
| Role | Active jobs | Share |
|---|---|---|
| Forward Deployed Engineer | 231 | 7.0% |
| AI Solutions Engineer | 215 | 6.5% |
| AI Go-To-Market Specialist | 68 | 2.1% |
| AI Research Engineer | 60 | 1.8% |
| Applied AI Engineer | 34 | 1.0% |
| AI Engineer | 31 | 0.9% |
| Customer Engineer | 30 | 0.9% |
| Data Engineer | 26 | 0.8% |
| AI Agent Engineer | 23 | 0.7% |
| Data Scientist | 19 | 0.6% |
| Technical Account Manager | 18 | 0.5% |
| Machine Learning Engineer | 17 | 0.5% |
Skills demand
Skill frequency is extracted from full job descriptions using pattern matching. The leaders are consistent with an application-layer market: Python, LLMs and RAG lead, with agent tooling (MCP, LangGraph, LangChain) already visible.
| Skill | Jobs mentioning | Share of all jobs |
|---|---|---|
| Python | 875 | 26.5% |
| Evaluation | 725 | 22.0% |
| LLM | 652 | 19.7% |
| AWS | 583 | 17.7% |
| AI Agents | 560 | 17.0% |
| Google Cloud | 507 | 15.4% |
| Azure | 498 | 15.1% |
| SQL | 482 | 14.6% |
| System Design | 473 | 14.3% |
| Spark | 350 | 10.6% |
| Java | 274 | 8.3% |
| Kubernetes | 260 | 7.9% |
| Observability | 244 | 7.4% |
| TypeScript | 241 | 7.3% |
| Fine-Tuning | 179 | 5.4% |
Remote work
460 of 3,302 tracked jobs (13.9%) are marked remote by the employer. Hybrid arrangements dominate for on-site-listed roles at frontier labs.
Salary disclosure
563 postings (17.1%) disclose a concrete salary range. Disclosure is concentrated in US-based employers, consistent with state pay-transparency laws.
Methodology & limitations
Dataset: active job postings collected from public employer career pages and ATS APIs (Greenhouse, Lever). Role classification uses exact-title pattern matching with evidence stored per posting; skills are extracted from description text.
Limitations: the dataset covers tracked employers only and is a lower bound on the market. Figures describe the tracked dataset, not the entire AI labor market. Salary figures use advertised ranges only.
Full details: data methodology.