Interview Prep
Role-by-role interview preparation. The cross-role All-Roles Guide covers the shared bar; the nine role guides below go deep, each with the same 11 components: core concepts · system design · debugging · coding · architecture · model selection · production incidents · portfolio project · 30-minute drill · 2-hour take-home · senior-level expectations.
The nine roles
| # | Role | Focus | Phases |
|---|---|---|---|
| 01 | LLM Application Engineer | Build LLM features/products on APIs | 1, 9, 10, 12 |
| 02 | LLM Platform Engineer | Gateways, routing, internal AI platform | 7, 8, 14 |
| 03 | AI Infrastructure Engineer | GPUs, scaling, deployment, cost | 6, 7 |
| 04 | Model-Serving Engineer | vLLM, throughput, latency, KV-cache | 6, 7 |
| 05 | RAG Engineer | Retrieval quality, grounding, RAG eval | 9, 12.03 |
| 06 | Agent Engineer | Tool use, agent loops, reliability, safety | 10, 14.01 |
| 07 | AI Coding Tools Engineer | IDE context, apply-patch, latency tiers | 11 |
| 08 | LLM Evaluation Engineer | Golden sets, judges, regression gates | 12 |
| 09 | AI Startup CTO | Product, moat, unit economics, team | 15 |
How to prepare (4-week plan per role)
- Week 1 — Concepts: master the role's "core concepts" + the linked phases; do the relevant exercises/.
- Week 2 — Build: complete the role's portfolio project (this is your differentiator — a working repo with numbers).
- Week 3 — Drill: do the 30-minute drill and system-design/debugging/incident questions out loud; practice the system-design template.
- Week 4 — Take-home + polish: complete the 2-hour take-home, mock interviews, and self-assess against senior-level expectations.
The universal bar (every role)
Interviewers across all roles probe the cross-cutting four: cost (per resolved task), latency (p95 under load), reliability (fallback/retries), safety (trust boundary, fail closed). And the meta-signal: every claim maps to a repo and a number. Don't say "I know RAG" — say "I built a RAG system; retrieval recall@5 was 0.82, generation faithfulness 0.91, p95 1.2s, $0.004/resolved query." That specificity is what makes a candidate impressive.
See also: the papers reading guide (the "10-paper interview core") and the cheatsheets/ for rapid recall.