Engineering Leader · Architect · Researcher
Cloud platforms, AI infrastructure, and enterprise systems for regulated, high-stakes environments.
Portfolio | Research | Writing | Podcast
- Cloud and Platform Engineering. Kubernetes-native architectures, cost governance, multi-cloud strategy. Production systems at scale with 99.99% availability across 100+ microservices.
- AI/ML Infrastructure. MLOps pipelines, inference platforms, retrieval-augmented systems. From model training through production deployment and monitoring.
- Enterprise SaaS. Full-stack product development. Schema-driven architectures, multi-tenant isolation, compliance workflows, and developer APIs.
- Micro-Containerized CPU Architecture (Patent Pending, USPTO App. 19/262,056) Orchestrating sub-core efficiency for AI workloads on standard compute.
- Retrieval-Native Language Models with Bayesian Attention (TechRxiv, 2025) Extending context windows via vector-native memory routing.
- Limitations and Ethics of AI Systems (TechRxiv, 2024) Analyzing architectural ceilings in transformer scaling.
- Aviation Climate Adaptation under Compound Risk (EarthArXiv, 2025) Quantifying cascading infrastructure failure in aviation networks.
- Enterprise SaaS (Stealth): Schema-driven platform for federal compliance workflows. Multi-tenant architecture, visual form builder, REST API.
- LocalRedact: Browser-native AI document redaction. PII detection via WebGPU. Zero uploads, zero servers.
- The Practical AI Digest: Weekly podcast breaking down applied AI for practitioners.
- Cornell University · MBA, General Management
- Dartmouth College · M.Eng, Electrical and Computer Engineering
- Penn State University · B.S., Software Engineering
"The boundaries where systems break and the economics of fixing them."