About
Software across distributed systems, data platforms, and AI.
The short version, in my own words.
Who I am
I’m a software engineer focused on distributed systems, data platforms, and infrastructure. My professional work spans source-level platform development, integrations, automation, release engineering, and production reliability across distributed data systems. The emphasis is on software engineering — writing and debugging the code these platforms run on — not just operating them.
How I work
I work across the lifecycle of a distributed data platform: distributed query / data platforms, Java and Python engineering, AWS + on-prem infrastructure, production reliability, CI/CD and infrastructure automation, and making heterogeneous data systems work together. I’ve also contributed to a professional agentic AI / security platform — repository / context ingestion, multi-step agent workflows, structured outputs, deterministic guardrail / policy evaluation, risk / impact analysis, and remediation workflows.
The AI bridge
My interest in AI infrastructure grew out of the same systems problems I already work on professionally: resource constraints, reliability, distributed components, APIs, observability, and performance. Professionally that shows up as agentic AI / security engineering. Personally it’s a self-operated heterogeneous LLM inference lab — inference engines, quantization, memory / context tuning, containerized deployment, and performance experimentation. The two are clearly separate tracks that share one engineering foundation.
Where I’m going
I’m drawn to increasingly complex engineering problems: distributed systems, platform engineering, data infrastructure, and AI infrastructure / AI platforms. The personal lab and the professional work run on the same discipline — memory budgets, throughput / latency tradeoffs, reliability, and observability — applied to ever larger systems. I’m looking to bring that to a team where the problems get harder, not simpler.
Education
Drexel University
Master of Science in Software Engineering
- Graduate Certificate in Software Architecture
- Graduate Certificate in Artificial Intelligence & Machine Learning
- Graduate Certificate in Software Security
The two tracks
- Professional — distributed data platforms + agentic AI / security
- Personal — hands-on LLM inference infrastructure lab