I design and deliver intelligent data and AI infrastructure, bridging principal-level engineering practice with peer-reviewed research and external technical leadership.

My work focuses on building reliable, governable, and observable systems for scientific and regulated environments—spanning agentic AI, data platforms, control planes, and emerging computational paradigms.

I am active across IEEE publications, conference presentations, technical writing, and open-source prototypes, translating research ideas into practical engineering approaches.

What I work on:

• Agentic AI infrastructure: semantic caching, control planes, lifecycle finite-state machines, and governed autonomy
• Security-critical patterns for autonomous and multi-agent systems
• Strategy and architecture for intelligent data services and Manufacturing Execution Systems
• Near-real-time telemetry, audit, provenance, and decision-record substrates across multi-terabyte environments
• Declarative policy, state, and intent expressed as code through custom resource models, GitOps, and control-plane patterns
• Technical mentorship and cross-functional influence across engineering, MLOps, SRE, and adjacent disciplines

I bring AIOps, MLOps, DevSecOps, and Site Reliability Engineering practices to systems that must remain reliable, explainable, and operable in regulated contexts.

My background spans distributed systems in high-reliability domains: reactive platforms in banking and finance, GxP-aligned pharmaceutical manufacturing systems, and industrial automation for semiconductor manufacturing.

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