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 101 tagged AI roles in Pharma. 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 |
|---|---|---|---|---|
| llm_observability | 31 | 10 | ↑+21 | |
| agent_orchestration | 34 | 19 | ↑+15 | |
| rag | 22 | 10 | ↑+12 | |
| model_serving | 26 | 15 | ↑+11 | |
| multimodal | 12 | 1 | ↑+11 | |
| fine_tuning | 18 | 8 | ↑+10 | |
| guardrails | 14 | 4 | ↑+10 | |
| vector_db | 10 | 3 | ↑+7 | |
| inference_infra | 9 | 5 | ↑+4 | |
| evals | 10 | 7 | ↑+3 | |
| agent_research | 7 | 6 | ↑+1 | |
| tool_use | 5 | 5 | ·0 |