01
Python services
Practiced inside a shared architecture with performance, reliability, and launch constraints.
Models, APIs, and product intelligence
AI Backend Engineering
Work on services, model integrations, APIs, and data flows that power an AI-backed B2C product.
What you practice
Work on inference, data pipelines, services, and the backend systems behind an AI-backed product.
Apply for Cohort 1
Program starts 13 July 2026.
02
Model integration
Practiced inside a shared architecture with performance, reliability, and launch constraints.
03
API design
Practiced inside a shared architecture with performance, reliability, and launch constraints.
04
Cloud and data flows
Practiced inside a shared architecture with performance, reliability, and launch constraints.
Backend work still has to survive review, traffic, and ambiguity.
Vague feature request
Every cycle starts with deliberate ambiguity, like a real backlog item.
Squad writes specification
Scope, tradeoffs, and acceptance criteria come before code.
Branch and build
Implementation happens on branches inside a shared codebase.
Open pull request
Work is submitted with tests, context, and merge rationale.
Review and judge
Peers evaluate quality, design, and production readiness.
Best pull request merges
The strongest contribution becomes the next product baseline.
Best fit for students or graduates from CS, AI, data science, or a similar program.