Principal Systems Architect — AI, Autonomy & High-Constraint Infrastructure
Systems architect, technical founder, and ML/software engineer with 7+ years building intelligent and distributed systems under difficult operational constraints. I specialize in ambiguous problems where architecture matters: real-time sensor AI, air-gapped ML infrastructure, adversarial distributed systems, agent and retrieval infrastructure, and 0→1 product platforms.
Selected wins with transferable outcomes.
Owned a vertical AI product from market thesis through architecture, implementation, tenant safety, QA, release infrastructure, production operations, packaging, and commercial evolution. Current platform scope includes 14 services, 171 migrations, 244 API routes, 73 dashboard pages, and 75 agent skills.
Read the case studyBuilt and operated a production storage platform from the ground up: anti-tamper verification, reliability/integrity guarantees, incentive system design, and real-time monitoring. Operated in production under continuous integrity proofs.
Led ML engineering for a real-time detection pipeline: signal processing + deep learning, optimizing accuracy/false-alarm tradeoffs and latency. Built simulation + synthetic-data workflows for robust training. Sustained sub-50 ms end-to-end inference on embedded hardware.
Owned end-to-end: data pipelines, training orchestration, deployment, and operator workflows in regulated environments. Reduced fine-tuning costs 65% via quantized adapters on commodity hardware.
Selected systems and research that demonstrate persistent context, auditable autonomy, and independent inquiry.
Selected roles focused on systems that have to remain reliable under adversarial, operational, or highly constrained conditions.
For the short version, download the résumé. For the fuller picture, use the Work and Research pages.