🔌 Career path

Gen AI Backend Engineer

Build the high-performance backend that serves LLMs: streaming, caching, async, state.

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20 labs · ~7.2h total

The engineer who makes GenAI products production-grade. Not prompt design - the systems
behind it: streaming token delivery, low-latency caching, asynchronous orchestration of
long-running jobs, and robust multi-turn state. You'll build these on Python and map each
to GCP (Cloud Run, Memorystore, Cloud Tasks/Pub-Sub, Cloud SQL + pgvector), then assemble
the whole stack in the end-to-end GenAI platform capstone.

Targets: Gen AI Backend Engineer / LLM Platform Engineer

🐧 Linux Administration Foundation

4 labs · ~2.1h · Open path →

Prerequisite foundations — skip if you already know this.

  1. 1. Command Line & Filesystem 🧪 Lab · 7 steps ○
  2. 2. Users, Permissions, Processes & Automation 🧪 Lab · 7 steps ○
  3. 3. Partitioning, Filesystems & LVM 🧪 Lab · 5 steps ○
  4. 4. Networked Filesystems with NFS 🧪 Lab · 5 steps ○
  5. 5. Linux Administration - Knowledge Check ❓ Quiz ○

🐳 Docker Foundation

7 labs · ~2.6h · Open path →

Prerequisite foundations — skip if you already know this.

  1. 1. Your First Container 🧪 Lab · 3 steps ○
  2. 2. Working with Docker Images 🧪 Lab · 5 steps ○
  3. 3. The Container Lifecycle 🧪 Lab · 5 steps ○
  4. 4. Building Docker Images 🧪 Lab · 5 steps ○
  5. 5. Container Networking 🧪 Lab · 4 steps ○
  6. 6. Volumes & Persistent Storage 🧪 Lab · 4 steps ○
  7. 7. Real-World Container Apps 🧪 Lab · 4 steps ○
  8. 8. Docker - Knowledge Check ❓ Quiz ○

🐍 Python for AI Foundation

3 labs · ~50 min · Open path →

Prerequisite foundations — skip if you already know this.

  1. 1. Python for Data Engineering 🧪 Lab · 3 steps ○
  2. 2. Python for AI Engineering 🧪 Lab · 3 steps ○
  3. 3. Python for Agent Engineering 🧪 Lab · 3 steps ○
  4. 4. Python for AI - Knowledge Check ❓ Quiz ○

🔌 Gen AI Backend Engineering

4 labs · ~1.1h · Open path →
  1. 1. Streaming LLM Tokens with SSE 🧪 Lab · 3 steps ○
  2. 2. Semantic Caching for Low-Latency LLMs 🧪 Lab · 3 steps ○
  3. 3. Async Orchestration & Task Queues 🧪 Lab · 3 steps ○
  4. 4. State Management for Multi-Turn AI 🧪 Lab · 3 steps ○
  5. 5. Gen AI Backend Engineering - Knowledge Check ❓ Quiz ○

📐 Vector Databases & Semantic Search

1 lab · ~20 min · Open path →
  1. 1. Vector Databases & pgvector 🧪 Lab · 3 steps ○
  2. 2. Vector Databases - Knowledge Check ❓ Quiz ○

🏗️ Capstone: End-to-End GenAI Platform

1 lab · ~20 min · Open path →
  1. 1. Build an End-to-End GenAI Platform 🧪 Lab · 3 steps ○
  2. 2. End-to-End GenAI Platform - Knowledge Check ❓ Quiz ○