I build production AI systems for high-stakes environments where failure has consequences.
15+ years building enterprise platforms. 7 years on Wall Street equities desks (Nomura VP, JP Morgan) taught me what production systems in regulated environments actually require—not demos, but infrastructure with policy enforcement, audit trails, and controlled execution. Most recently: applying that discipline to AI platforms for defense contractors.
I focus on the gap between AI capabilities and production readiness. Enterprises need governance layers, orchestration systems, and execution controls that make LLMs deployable in finance, defense, and other regulated industries.
Core Expertise:
Event-driven architecture • API orchestration • Service boundaries & contracts • Stakeholder engagement & cross-functional delivery • AI governance & policy enforcement • Agentic systems • Execution control & workflow reliability • RAG pipelines • Production observability
Featured System
AI Policy Governance Platform
Enterprise AI control plane with pluggable policy enforcement, dual-checkpoint validation, full audit trails, and human-in-the-loop workflows.
Architecture: Event-driven • Microkernel (plugin-based) • Policy-gated orchestration
Built for: Regulated industries requiring auditability, compliance, and controlled AI execution.
Production Use Cases: Finance: MNPI firewall, data redaction, client communication review • Healthcare: HIPAA compliance (future) • Government: Data sovereignty enforcement (future)
Other Systems
RAG Knowledge Assistant
Converts plain English queries to validated SQL with automatic schema selection, security checks, and dynamic result visualization. Reduces analyst query time from hours to minutes.
NLP-to-SQL Dashboard
Production RAG system with query filtering and semantic retrieval for DoD training documentation. Optimizes precision through multi-stage reranking and domain-specific embeddings.
API Gateway
API Gateway for multi-model LLM orchestration with circuit breakers, retry logic, adaptive rate limiting, and intelligent fallback routing. Handles request validation and traffic shaping for production AI workloads.
Technical Work and Insights
Technical Writing and ADRs (coming soon)
├─ Policy Outcome Model Design
Framework for modeling and evaluating policy outcomes in AI governance systems.
├─ Sync vs Async Communication Patterns
Decision framework for choosing synchronous vs asynchronous communication in distributed AI systems.
├─ Modular Monolith to Microservices Strategy
Migration approach for evolving monolithic AI platforms into distributed microservices architecture.
└─ How the Governance Platform scales 10x → 1000x
Documenting the evolution and scaling challenges of AI governance platform.
Case Studies
├─ NLP-to-SQL Interface for Enterprise Databases
Enables non-technical users to query enterprise databases in plain English with validation and visualization, reducing analysis time from hours to minutes.
└─ RAG-Powered Document Intelligence System
Production RAG system providing instant, context-aware access to enterprise documentation with semantic search and source attribution.
Contact
Memphis, TN | Previously New York, NY
Senior Systems Engineer, Solutions Architect roles | Open to relocation