Building reliable data infrastructure, distributed systems, and applied AI tools.

Data Infrastructure & Applied AI Engineer
10+ years of experience designing distributed systems, cloud data platforms, and practical AI software.

I’ve worked across consulting, enterprise, and research-oriented environments — including Deloitte, Maersk, Oticon, and Deep AI Mind — building systems in data engineering, infrastructure, and applied AI.

My work sits at the intersection of data platforms, systems architecture, and intelligent software. I’m especially interested in AI systems that are useful, controllable, and production-aware.

I enjoy taking projects from early concept to working implementation, with a focus on reliability, clarity, and strong engineering foundations.

• ClarityClaw
  AI agent runtime and orchestration platform focused on traceability, controlled execution, and safe tool integration.

• MacShell
  Experimental local AI shell assistant for macOS using local LLMs, with confirmation gates and safety checks.

• HeartSignal (Private)
  Real-time heart sound recording and visualization prototype built with Python and audio DSP.

• Clinical LLM (Private)
  Local LLM-based assistant for diagnostic reasoning and treatment support workflows.

Data Infrastructure & Distributed Systems
Apache Spark • Ray • Kafka • Airflow • Hadoop • AWS • GCP • Azure • Data Lakes • Parquet • Batch & Streaming

Programming
Python • SQL • Java • Rust (exploring)

Applied AI
LLMs • agent systems • LoRA fine-tuning • CNNs • local AI workflows • applied AI APIs

Strengths
System architecture • scaling • performance tuning • production debugging • research-to-engineering execution

AI agent runtimes • local AI tools • data platforms • distributed systems • applied AI prototyping