Software Developer to AI Engineer: A Practical Roadmap
Updated 2026-10-15
Short answer
Developers already have most of what AI engineering needs. Add: LLM API usage, retrieval-augmented generation, evaluation and testing of model output, basic ML concepts, and deployment/monitoring. Prove it with two or three shipped projects.
Roadmap
A realistic 3–6 month part-time sequence:
- Month 1: LLM APIs, prompting, structured output
- Month 2: Embeddings, vector search, RAG pipelines
- Month 3: Evaluation, guardrails, cost and latency tuning
- Month 4+: ML fundamentals, fine-tuning basics, MLOps
- Throughout: ship public projects and write about them
Related programs
- Diploma in LLM Systems & RAG Engineering$399 CAD · self-paced
- Diploma in Applied Machine Learning$399 CAD · self-paced
- Diploma in Data Engineering for AI$399 CAD · self-paced
Training a team? Seats are $199 each · Not ready? Try the free 7-day course
Common questions
- Do I need a math degree?
- No for applied AI engineering. Linear algebra and statistics basics help for deeper ML work.