AI & Machine Learning Engineering
Building, fine-tuning, and shipping models — LLMs, RAG pipelines, vector search, and ML systems that run reliably in production.
The capabilities I bring to every engagement as a Microsoft architect — spanning AI, multi-cloud, security, and modern software delivery, applied across commercial and government platforms.
Building, fine-tuning, and shipping models — LLMs, RAG pipelines, vector search, and ML systems that run reliably in production.
Designing autonomous agents, tool-calling workflows, evaluation rubrics, and reusable prompt systems tuned for consistent, trustworthy output.
Designing resilient landing zones and workloads across Azure, AWS, and GCP with cost, security, and scale baked in from day one.
CI/CD pipelines, Infrastructure as Code, Kubernetes, and internal developer platforms that make shipping fast, safe, and repeatable.
Threat detection, identity-first security, secure-by-design architecture, and zero-trust controls across cloud and edge environments.
Real-time and batch pipelines, lakehouse design, streaming, and the governed data foundations that AI and analytics depend on.
End-to-end product delivery with TypeScript, modern frameworks, and clean API design — from data model to polished user experience.
Keeping systems fast and available at scale — SLOs, telemetry, incident response, and observability that turns noise into insight.
Pushing intelligence to the edge — on-device inference, IoT, and early quantum readiness for the next wave of compute workloads.
A cinematic control surface for a place where machines forecast sentiment, light behaves like code, and every skyline is quietly negotiating with the future.
Three generated live frames render like synthetic photographs: industrial glow, rain-smeared optics, and machine hallucination layers that react to your pointer.
Adjust the synthetic city: increase signal intensity, change anomaly pressure, and move across the map to bend the threat field in real time.