AI/ML Fundamentals for Architects
2-3 weeksSkills You'll Build
Machine learning concepts (architect perspective)How LLMs and AI models workAI workload characteristicsResource requirements for AIAI system architecture patterns
Cloud Architect → AI Platform Specialist
Cloud Architect to AI Platform Specialist: From Cloud to AI Infrastructure
Your cloud architecture expertise is perfect for AI platform engineering. This path leverages your understanding of scalable infrastructure, managed services, and architecture patterns to build AI platforms. Move from designing cloud solutions to architecting AI-powered platforms.
3-5 months
Prerequisites
- Experience as a cloud architect or solutions architect
- Deep knowledge of AWS, Azure, or GCP
- Understanding of microservices and distributed systems
- Experience with infrastructure as code
- Familiarity with containerization and orchestration
Your Learning Path
Cloud AI Services Deep Dive
3-4 weeksSkills You'll Build
Azure AI services and OpenAI integrationAWS Bedrock and SageMakerGoogle Cloud AI PlatformManaged vs self-hosted AI tradeoffsCost optimization for AI workloads
LLM Integration and APIs
2-3 weeksSkills You'll Build
OpenAI and Claude API integrationAPI gateway patterns for AIRate limiting and quota managementMulti-model architecturesFallback and redundancy patterns
AI Platform Architecture
3-4 weeksSkills You'll Build
Designing AI platformsVector database infrastructureModel serving architecturesFeature stores and data pipelinesMulti-tenant AI platforms
AI Platform Operations
2-3 weeksSkills You'll Build
MLOps and AI operationsMonitoring and observability for AICost management at scaleSecurity and complianceDisaster recovery for AI systems
Portfolio and Career Positioning
2-3 weeksSkills You'll Build
Building AI platform portfolioShowcasing architecture expertiseAI platform specialist interviewsNetworking in AI platform communityPositioning cloud experience for AI