Career transition
Backend Engineer to AI Engineer
Backend engineers already understand APIs, data flow, reliability, and production trade-offs. The gap is learning how model behavior changes system design.
What already transfers
- API design
- Databases
- Observability
- Production reliability
- Security basics
Likely gaps
- Embeddings
- RAG
- Evaluation
- Prompt/system design
- Model cost and latency
Do not waste time relearning
- Beginner programming courses
- Generic software architecture basics
- Toy-only AI demos
Suggested progression
- LLM API integration
- Embeddings and vector search
- RAG with citations and failure handling
- Evaluation datasets and regression checks
- Production AI feature with monitoring
Readiness evidence
- A model-backed feature with fallbacks
- A small eval suite that catches bad answers
- Latency and cost notes
Related learning
Turn this into today's learning plan.
Roe turns an outcome into the next useful lesson, then checks and reviews what sticks.
