AI Engineer Roadmap
The AI engineer roadmap is a structured path for learning how to build real Gen AI applications: model APIs, prompts, RAG, agents, evaluation, and production architecture.
What it is
A step-by-step path from programming foundations to production AI systems.
Why it matters
AI engineers need breadth: APIs, prompts, retrieval, agents, evaluations, deployment, cost controls, and security.
How it works
Move through foundations, LLM concepts, API layer, prompt engineering, embeddings, RAG, agents, LangChain, evaluation, and production.
Common mistakes
- Skipping API basics.
- Jumping to agents before RAG and evals.
- Building demos without deployment and monitoring.
Best practices
- Build a project per phase.
- Log outputs and costs early.
- Turn roadmap topics into portfolio artifacts.
FAQ
How long does it take to become an AI engineer?
A focused beginner can build useful projects in 8-12 weeks, then deepen production skills over several months.
What should I build first?
Start with an LLM API chatbot, then add streaming, structured output, RAG, and one tool call.
Keep Learning
Use the interactive AI Engineer Roadmap to turn this concept into a practical project path.
Open Roadmap