Designing AI Systems That Scale: A Training Course in Architecture and Governance for Leaders (Online / Remote)
1Summary
An AI system that works well in a pilot often collapses the moment it needs to scale across an enterprise — the architecture was never designed for governance, compliance, or growth in the first place. This training course is built for the technical leaders who make that call: how to architect AI systems that stay scalable, governable, and aligned with regulation as they grow.
Delivered by the Arab British Fellowship Training Academy, the programme combines theoretical grounding with practical tools for designing, deploying, and governing AI systems enterprise-wide, using real-world case studies to unpack the complexity of today's AI environments. It covers the technical standards, cloud-native architecture patterns, and regional governance frameworks needed to build platforms that hold up in production, not just in a demo.
2Objectives and target group
Who Should Attend?
- Technical Programme Managers and Technical Project Directors leading AI initiatives
- Cloud Architects and AI Platform Engineers designing AI solutions
- DevOps Leaders and MLOps Engineers managing AI infrastructure and pipelines
- Infrastructure Managers overseeing AI systems
- Security Architects handling AI security
Major objectives of this training course:
- Build a strategic view of AI architecture, including how data, machine learning models, and deployment fit together to align with an organisation's vision.
- Understand the global AI regulatory landscape and adaptive governance strategies for AI methods.
- Gain practical skills in AI risk assessment and compliance.
- Design custom governance programmes suited to different organisations.
- Work through real-life case studies set in organisational context.
3Course Content
Module 1: Architecture Choices and Regional Policy Context
- Enterprise AI Architecture Patterns
- Cloud vs On-Premise AI Infrastructure
- Saudi Cloud First Policy (verified)
- UAE TRA's actual published guidelines
Module 2: Building the Platform
- Model Development Platforms
- Data Pipeline Architecture
- API Management
- Microservices Architecture
Module 3: Governing and Operating at Scale
- Architecture Review Boards
- Change Management Processes
- Performance Monitoring
- Capacity Planning
Module 4: Delivering, Testing and What Comes Next
- Continuous Integration/Deployment
- A/B Testing Frameworks and Testing Strategies
- Performance Testing
- Emerging Trends: Edge AI Architecture and Federated Learning Systems