Tech-tag co-occurrence
Every AI role gets tagged from a 35-term controlled vocabulary spanning agent / eval / training / inference / modality clusters. Tags that frequently appear together in the same JD pull each other close; thicker edges = more co-occurrences. The clusters that emerge organically are the real sub-disciplines of applied AI engineering right now.
All sectors · 4742Enterprise · 1275AI Frontier · 868Industrial · 650Data AI · 526Consumer · 337Banking · 239Fintech · 220Robotics · 127Defense · 115Pharma · 101Media · 73Retail · 62Hospitality · 62Telecom · 27Seattle · 27Aerospace · 14Insurance · 12Healthtech · 7
Showing 62 tagged AI roles in Hospitality. Layout is a Fruchterman-Reingold force simulation, run server-side to convergence.
Tag velocity · last 4 weeks vs prior 4
Which technologies are hot, which are cooling. Sparkline = 12 weeks of unique roles tagged with each term, last bar on the right is this week. Sorted by absolute pickup. Tags with under 10 lifetime mentions are hidden as noise.
| Tag | 12-week trend | Last 4w | Prior 4w | Δ |
|---|---|---|---|---|
| agent_orchestration | 35 | 0 | ↑+35 | |
| model_serving | 33 | 2 | ↑+31 | |
| llm_observability | 24 | 0 | ↑+24 | |
| rag | 23 | 0 | ↑+23 | |
| recommender_systems | 22 | 1 | ↑+21 | |
| inference_infra | 15 | 1 | ↑+14 | |
| guardrails | 14 | 0 | ↑+14 | |
| vector_db | 12 | 0 | ↑+12 | |
| fine_tuning | 12 | 0 | ↑+12 | |
| tool_use | 11 | 0 | ↑+11 |