AI Governance & Risk
- AI readiness and risk assessments
- Control frameworks aligned to policy obligations
- Human-in-the-loop oversight models
- Traceability and explainability patterns
Capabilities
Governance-first AI delivery.
A consulting model focused on practical implementation of AI governance in regulated operating environments.
Cloud & Platform Architecture
- Cloud-native and event-driven architecture
- Secure access models (RBAC and zero-trust principles)
- Observability, audit logs, and production resilience
- Operational controls for AI-enabled platforms
GenAI Operating Model
- Secure retrieval-augmented generation (RAG)
- Governed AI agent orchestration
- Lifecycle management and controlled release practices
- Policy-to-engineering translation across teams
Delivery Leadership
- Architecture and engineering alignment
- Risk and compliance stakeholder collaboration
- Governance-aware modernization programs
- Hands-on guidance for distributed teams
Reference Framework Alignment
Advisory approach reflects practical alignment with recognized AI governance and risk frameworks, including NIST AI RMF principles and AI management system practices.
Leadership Profile
Founder and principal advisor with over two decades of engineering and architecture leadership across highly regulated sectors. Focused on helping organizations implement AI governance in a way that is practical, risk-aware, and sustainable.
Experience includes enterprise modernization, cloud-native architecture, secure access models, compliance-sensitive workflows, and governed AI system design, with remote advisory support across the USA, Europe, and the Middle East.
Credentials
Architecture
Certified Azure Solutions Architect Expert with extensive cloud-native system design experience.
Governance
Practical alignment with established AI risk and governance principles for enterprise adoption.
Delivery
Hands-on leadership across engineering, risk, and compliance teams to operationalize governance.