Build the platformML teams ship on.
Multi-tenant LLM serving, model registries, feature stores, drift monitoring. The platform layer that makes production AI actually work — and the work that gets you to staff.
What you'll actually be able to do.
Not "you'll know about Airflow." What you'll ship, debug, and defend in an interview.
You’ll be the person who
- Design multi-tenant LLM serving with isolation
- Run inference at scale without the 3am page
- Build feature stores other teams trust
- Attribute AI cost per team and bring the bill down
- Survive prompt injection and audit on day one
And the market pays you for
The system you'll build by the end.
A production reference architecture — not a toy demo. Every node maps to a course or project in this path.
From week one to capstone.
A realistic 5-stage timeline. Go faster if you already have pieces; slower if you're brand new.
- 01Week 1–4
DE refresher
Airflow, dbt, containers — fast
- 02Week 5–10
AI data + retrieval
Embeddings, hybrid retrieval, evaluation
- 03Week 11–16
Serving + features
BentoML, Triton, vLLM, Feast online/offline
- 04Week 17–22
Multi-tenant platform
K8s, RBAC, cost attribution, audit
- 05Week 23–28
Ship capstone
Multi-tenant LLM platform with audit + injection defense
One project, endlessly talkable.
Every path ends with a flagship capstone you'll ship, write up, and walk through in every interview loop.
The capstone that takes you from senior DE to staff AI platform.
What you’ll ship
- 01Multi-tenant LLM with per-team isolation
- 02Model registry + audit trail for every prompt
- 03Cost attribution per team / per model / per call
- 04Prompt-injection defense + secrets isolation
- 05p95 < 300ms under real traffic, with autoscale
Questions you'll confidently answer.
These are real interview questions for AI Platform Engineer roles. If you can answer all four with a story from your capstone, you're ready.
Design isolation between two teams sharing one inference cluster
Walk me through cost attribution for an LLM platform with 50 endpoints
How do you monitor model quality without label feedback?
Design the rollback path for a model that breaks an SLO mid-day
Stack you'll learn.
Not memorized — operated. Each tool is taught inside a project, not an isolated lecture.
Start building your first system — today.
Module 01 is free. No card. Ship something real this weekend.