14+ years building AI/ML platforms, distributed systems, cloud infrastructure, healthcare software, commerce products, and fintech systems—plus 5 years of Solutions Engineering experience translating complex systems into clear business outcomes.
I work at the intersection of software engineering, AI systems, and product delivery.
My experience covers architecture, implementation, testing, deployment, monitoring, and production improvement across several industries. I focus on systems that are maintainable, measurable, and understandable—not only impressive in a demo.
I also translate architecture, platform capabilities, technical risks, and tradeoffs into executive-ready presentations and technical narratives for both engineering and non-technical audiences.
Observability, failure handling, testing, rollout, and rollback belong in the design.
Retrieval, deterministic rules, validation, retries, and human review keep model behavior controlled.
Choose the language, database, and infrastructure that fit the workload instead of forcing a favorite stack.
Lead architecture and delivery of AI-powered commerce workflows. Build multi-step agent systems with controlled retrieval, tool execution, validation, retries, and human review. Developed an AI Content Agent that reduced a workflow from roughly 35 minutes to well under one minute.
Built ML workflows, inference services, evaluation systems, continuous-learning capabilities, and MLOps foundations spanning experimentation, deployment, monitoring, governance, drift, explainability, fairness, and operational readiness.
Designed enterprise data platforms across AWS, Azure, and GCP. Built batch, streaming, lakehouse, and event-driven systems with Spark, Databricks, Kafka, Snowflake, Python, Go, and infrastructure automation.
Modernized healthcare backend systems, interoperability services, and clinical-document workflows using Java/Spring Boot, .NET, Python, React, HL7, FHIR, asynchronous processing, and ML-assisted classification.
Built payment-platform capabilities across merchant apps, APIs, transaction processing, webhooks, PayPal/Venmo integrations, tokenization, PCI-oriented security, retries, idempotency, settlement, and refunds.
A multi-step agent workflow combining catalog intelligence, retrieval, deterministic business rules, generative models, validation, retries, and human review.
Reduced a product-content workflow that previously required roughly 35 minutes to well under a minute.
Commerce AI, enterprise machine learning, cloud/data platforms, healthcare interoperability, and payment infrastructure.
Review systems for correctness, maintainability, observability, security, failure handling, and unnecessary complexity.
Guide engineers through system design, debugging, production incidents, rollout strategy, technical risk, and release readiness.
Translate technical architecture and product tradeoffs into polished PowerPoint decks, diagrams, proposals, and decision-focused narratives.
Georgia Institute of Technology
Georgia Institute of Technology
I’m interested in senior engineering work where AI, software architecture, distributed systems, and product execution meet.