A hands-on, role-based curriculum for the AI Engineering career ladder.
The content in these repositories is generated with AI assistance and undergoes ongoing human review. It may contain errors or outdated information. Treat it as a learning resource: cross-reference official docs, test code in a safe environment, and report issues via GitHub Issues or Discussions.
| Role | Level | Repositories |
|---|---|---|
| Agentic AI Developer | L20 | 📘 Learning · ✅ Solutions |
| LLM Application Developer | L20 | 📘 Learning · ✅ Solutions |
| Agentic AI Engineer | L30 | 📘 Learning · ✅ Solutions |
| AI Evaluation Engineer | L30 | 📘 Learning · ✅ Solutions |
| Applied AI Engineer | L30 | 📘 Learning · ✅ Solutions |
| RAG & Retrieval Engineer | L30 | 📘 Learning · ✅ Solutions |
| Senior Agentic AI Engineer | L40 | 📘 Learning · ✅ Solutions |
| Agentic Systems Architect | L48 | 📘 Learning · ✅ Solutions |
See the Career Progression Guide for the full ladder — level descriptions, skills matrix, compensation ranges, promotion criteria, and specialist tracks.
One of five sibling orgs in the AI Career Curriculum ecosystem, organized by what you do relative to a model:
- AI Infrastructure Curriculum — run the platforms (Kubernetes, GPUs, training infra, serving, MLOps, IaC, SRE).
- ML Engineering Curriculum — build & train the models (data, fine-tuning, pretraining, RLHF, evals).
- AI Engineering Curriculum (you are here) — build with the models (agentic apps, RAG, multi-agent systems).
- AI Governance Curriculum — govern & assure AI (security, compliance, evaluation, safety).
- AI Startup Curriculum — turn it into a company — the startup operating school for technical founders (functional curricula × role pathways × stages).
Maintained by VeriSwarm.ai