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AI·Intermediate36k learners

AI Engineer

Target role — Applied AI

Build, evaluate and ship applications powered by modern LLMs — with the engineering judgment to make them reliable.

By the end, you'll have shipped
A deployed LLM-powered productA RAG system over real documentsAn agent with tool useAn evaluation harness with metrics
Career insight
Live market data · Curated baseline
7,400+
Open roles
active openings, last 30 days
$155k
Median salary
$110k–$220k · US median base, mid-level
Surging demand
Hiring demand
fastest-growing engineering title
No degree required
Typical entry
Shipped AI products outweigh credentials
Most-requested skills
Cloud
Related roles
ML EngineerSoftware EngineerResearch EngineerSolutions Architect
The path · 5 stages · 18 checkpoints

Stage progression

1
Python & ML Foundations

Solid Python plus just enough ML theory to reason about model behaviour.

0/3 checkpoints5–7 weeks
Production Python
2.5 weeks
How LLMs Work
2 weeks
Working with Model APIs
APIs1.5 weeks
2
Prompting & Context Engineering

The highest-leverage skill: shaping what goes into the model.

0/4 checkpoints3–4 weeks
3
RAG & Knowledge Systems

Ground models in your data: retrieval, chunking, reranking.

0/4 checkpoints5–6 weeks
4
Agents & Tool Use

Models that act: tools, loops, multi-step work and the protocols emerging around them.

0/4 checkpoints4–5 weeks
5
Ship & Job Search

Deploy, monitor and prove it — then convert the portfolio into offers.

0/3 checkpoints4–6 weeks