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Expert3 to 5 days / 20+ guided hourspublished
AI Engineer Career Path: Expert
Architect production AI workflows with security controls, model routing, cost controls, and capstone automation.
Audience
- Self-paced technical learners
- Instructor-led cohorts
- Enterprise teams preparing staff for hands-on operations
Prerequisites
- Intermediate course or equivalent production experience
- Comfort with troubleshooting and design tradeoffs
Outcomes
- Provision an isolated ai engineer career path lab from template metadata.
- Use snapshots, rollback, validation checks, and teardown safely.
- Explain how LiteLLM, Ollama, Qdrant, Python fit into an enterprise training environment.
- Produce evidence that an instructor or admin can review.
Course plan
Modules and labs
Each module maps to provisioned lab work, validation evidence, reset/rollback policy, and instructor visibility.
Required templates
Python data science workstation
definedUbuntu 24.04 LTS
Vector database/RAG node
definedUbuntu 24.04 LTS plus Qdrant or compatible vector DB
Ollama/LiteLLM client node
definedUbuntu 24.04 LTS
Validation checks
Notebook reachable
JupyterLab returns a valid login page or authenticated health response.
AI endpoint reachable
The model gateway returns at least one allowed model for the tenant.