The AI Architect Roadmap

Most portfolios list projects. This one proves the roadmap.

There's a well-known 15-step roadmap serious people study to become an AI architect — role fundamentals, cloud infra, RAG, agent systems, MLOps, governance, all the way through interview readiness and career growth. Below is that exact roadmap, with a real, checkable proof point at every step: a live platform, a real ADR, a real deployed-and-torn-down cloud stack — not a claim.

18 open-source repos · 29 documented ADRs · 17 live products

Understand the AI Architect Role

AI system thinking, business alignment, architecture mindset

Positioning + executive brief

Learn AI & Machine Learning Fundamentals

Core AI/ML concepts every architect must understand

5 agent-pattern reference repos (ReAct, Reflection, Plan-Execute, Multi-Agent, Swarm)

Master Data Foundations

Designing AI systems starts with reliable data

Real ingestion data contract + lineage metadata, enterprise_rag_platform

Learn Cloud & Infrastructure Basics

Cloud-native infrastructure for AI systems

Real AWS ECS Fargate + RDS + ALB and GCP Cloud Run + Cloud SQL — deployed, verified, torn down

Understand Deep Learning

Building blocks behind modern AI models

vLLM Architecture Lab — real PagedAttention + continuous batching + KV cache simulator

Learn Generative AI & LLMs

How modern AI applications are built

Real per-call token pricing + budget enforcement, not guessed cost — agent-finops

Learn RAG & Knowledge Systems

Key milestone

Building AI systems that use trusted business knowledge

Enterprise RAG Platform — authorization before ranking, not after generation

Master AI Architecture Patterns

Choosing the right architecture for the right use case

15 ADRs across the org — orchestration vs. governance, PaaS vs. IaC, build vs. buy

Build AI Agents & Workflows

Moving from simple chatbots to action-taking AI systems

AegisAI (governance), VAP (orchestration), AegisLoop (mission fleets) — 3 live platforms

Master MLOps & LLMOps

Making AI systems production-ready

golden-eval-registry as a real CI gate — found and fixed a fixture bug on first real execution

Learn Security, Privacy & Governance

Designing safe and trustworthy AI systems

Org-wide auth-gate hardening pass across 6 repos, 2026-07-03/04

Study AI System Design Case Studies

Learning how real AI systems are structured

Enterprise case studies — Lucid Motors (10→2 staffing), Volvo Cars payments + EDI

Build Your AI Architect Portfolio

Showing architecture thinking, not just coding skills

This site — 17 live products, 18 open-source repos, 29 documented ADRs

Master AI Architect Interviews

Explaining decisions clearly and practically

ai-architect-interview-playbook — system design, cloud architecture, STAR, and trade-off content grounded in real shipped decisions

Grow Your AI Architecture Career

Becoming a strategic AI leader, not just a technical expert

Bidirectional MCP + real A2A protocol wiring — the org's answer to 2026's agentic-AI trend

Want to see how I'd explain any of this out loud?

Step 14 above links to a dedicated repo — system design questions, cloud architecture trade-offs, STAR-method behavioral write-ups, and scalability/governance reasoning frameworks, all grounded in the real decisions this roadmap points to, not generic interview prep.

Read the interview playbook

See the full architecture portfolio