Senior Engineer · Production AI with Guardrails · Financial & Enterprise Platforms
I build production-grade AI in data-rich, compliance-aware environments — RAG pipelines, multi-agent workflows, document-intelligence copilots, and LLMOps with guardrails. With 20+ years across backend engineering, database platforms, and mission-critical financial systems, I focus on secure, high-availability data platforms and modernizing legacy integrations into reliable, service-oriented architectures.
GenAI / LLM
- RAG systems with semantic retrieval, source citations, and low-confidence fallbacks
- Agentic workflows with LangGraph (validate → analyze → summarize)
- AWS Bedrock integration with structured JSON guardrails and hallucination reduction
- LLMOps: CI/CD, evaluation frameworks, observability (Langfuse), and responsible AI practices
Platforms & delivery
- Python production services, REST APIs, and cloud-native microservices on AWS
- SQL Server / Oracle performance tuning, ETL validation, and incident response
- Legacy modernization (ColdFusion, Lucee, BoxLang, ColdBox) into scalable service-oriented architectures
AI / ML · Python · LangChain · LangGraph · LlamaIndex · Hugging Face · RAG · vector stores · AWS Bedrock · pytest
Cloud & infrastructure · AWS Lambda · S3 · DynamoDB · API Gateway · Step Functions · Docker
Data & backend · pandas · NumPy · SciPy · SQL Server · Oracle · PostgreSQL · T-SQL · REST · microservices
Application platforms · TypeScript · React · Node.js · Java
Engineering practices · SSMS · SQL Agent jobs & monitoring · source control & deployment · technical documentation · mentorship & technical leadership
- Reliability over cleverness — especially in regulated systems
- Guardrails before demos — structured outputs, citations, and human review paths
- Performance is a design decision, not a last-minute fix
- Code should be understandable by the next engineer
Above all, I value clarity, correctness, and operational safety over shortcuts.
