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Architect

AI Architect

Design AI systems that survive a security review, a budget cycle, and a year in production.

Who this is for

Solution and enterprise architects who own the shape of the system, not just a service.

What you should be able to do

Produce a reference architecture with an explicit trust boundary, a cost model, and a rollout plan someone else can execute.

Career ladder

The titles this track maps onto. Levels differ between companies. The useful part is the direction, and what each step adds to the one before it.

  1. Junior AI Solutions Architect
  2. AI Solutions Architect
  3. Senior AI Architect
  4. Principal AI Architect
  5. Chief AI Architect

Tech stack

What the work is actually done with. Grouped by the job each tool does, so the list reads as a system rather than a pile of names.

Cloud
AWSAzureGCP
Runtime
KubernetesTerraformDocker
AI
BedrockAzure OpenAIVertex AIRAGMCP
Cross-cutting
IAMZero TrustEvent-driven designCost modelling

The delivery flow

The order the work actually happens in. Each step is where a decision gets made and written down, not a chapter heading.

  1. Business problem
  2. Reference architecture
  3. Trust boundary + IAM
  4. Data + retrieval layer
  5. Model / agent layer
  6. Deployment topology
  7. Cost model
  8. Rollout plan

Reference repository structure

A starting layout for this track. The directories are the ones that get added late and hurt. Decisions, evals, policy, lineage. Promoted to the top level where they are visible.

reference-architecture/
├── context/               # C4 level 1 - systems and actors
├── containers/            # C4 level 2 - deployable units
├── decisions/             # ADRs, one file per decision, numbered
│   └── 0001-why-rag-not-finetune.md
├── diagrams/              # source, not exported images
├── threat-model/          # STRIDE per trust boundary
├── cost/                  # per-environment model and assumptions
├── infrastructure/        # terraform, per environment
└── rollout/               # phases, exit criteria, rollback

Reading path

12 published guides on this track. Every one is a live page on this site. Nothing here is a placeholder.

  1. Building an Enterprise AI Stack in 2026: Architecture That Actually Ships
  2. Zero Trust Architecture: The Complete Implementation Guide for Multi-Cloud Environments
  3. AI Security Architecture: Protecting LLMs, Data Pipelines, and Model Endpoints
  4. Cloud Services, Architecture to Deployment [2026]
  5. Data Engineering for AI: The Pipeline Architecture Every ML Team Needs
  6. What Are Governed AI Agents? Definition, Architecture and Why They Matter [2026]
  7. Zero Trust Architecture for Nigerian Government Cloud
  8. Zero Trust Architecture on AWS: Step-by-Step Guide
  9. Zero Trust Architecture: Complete Implementation Guide [2026]
  10. AWS SAA vs Azure AZ-305: Which Cloud Architect Certification Pays More in 2026?
  11. AWS Solutions Architect Associate (SAA-C03) Exam Cheat Sheet, 2026, Citadel Cloud Management
  12. AWS Solutions Architect Salary 2026: SAA-C04 ROI Analysis

Reference implementations

Citadel’s open-source repositories for this track. Terraform modules, MCP servers, and reference architectures you can read, fork, and run. Apache/MIT licensed; check each repository for its terms.

Primary sources

The standards, framework documents, and vendor references this track is built against. Go here when you need the authoritative wording rather than a summary. In a security review or an audit, the source is what counts.

Other tracks

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