Expertise
Systems behind
the signal.
I work across AI adoption, engineering leadership, cloud architecture, and operational workflow—turning emerging capability into systems teams can deliver and trust.
Each area connects a clear point of view with public-safe evidence from real product and engineering work.
Areas of practice
Seven connected capabilities. One delivery system.
01
AI transformation · Engineering operating model
Agentic SDLC governance
Designing accountable operating models for coding agents, from planning and execution through validation, escalation, and evidence.Plan → ProveLifecycle control02Leadership · Adoption · Delivery systems
Engineering leadership and AI adoption
Helping engineering teams adopt AI through clear direction, coaching, dependable delivery practices, and evidence of what changed.Adopt → ScaleTeam capability03Cloud-native engineering · Microsoft platform
Azure and .NET cloud architecture
Architecting cloud-native products and modernization paths with Azure, .NET, event-driven services, and security-by-design.Design → DeliverCloud architecture04Applied AI · Traceable workflow
Healthcare AI and regulated workflows
Connecting AI-generated transcription, facts, and clinical documents to reliable workflows for review and downstream action.AI → ActionWorkflow integration05Product rescue · Performance · Cloud migration
Legacy modernization and performance engineering
Restoring confidence in live products while creating a measured, security-minded path toward modern architecture.10×Measured response gain06AI products · Event-driven value
Applied AI and computer vision
Turning machine-learning and computer-vision signals into useful customer experiences and business workflows.See → ServeApplied intelligence07Enterprise workflow · Legal tech · BPM
Workflow platforms and legal technology
Designing workflow, forms, integration, and SaaS capabilities across legal technology, healthcare, and enterprise operations.Flow → OutcomeOperational systemsConnect the capabilities