Career¶
The non-technical half of becoming an AI engineer: roles, portfolio, visibility.
The role landscape (2026)¶
| Role | What it actually is | Prep emphasis |
|---|---|---|
| AI Engineer | Product engineer who ships LLM features | Courses 06–13, projects |
| Agent Engineer | Builds/tunes agentic systems and harnesses | Agent Engineering track, evals |
| ML Engineer | Training, fine-tuning, infra | Courses 03–05, 15 |
| Applied Researcher | Bridges papers → product | Deep dives, papers |
Standing out¶
- Ship 2–3 public projects from Build These First — deployed, with eval numbers in the README.
- Write about what broke. Postmortems of your own agent failures outperform tutorial-rehash posts.
- Contribute to open source — this handbook counts: contribute.
When you land interviews¶
Head to Interview Prep.
Work in progress
This page is a scaffold — worked examples and depth are being added. Want to help? Grab a good first issue or read the contribution guide.