I’m an Applied AI Engineer focused on building end-to-end, production-ready AI systems — from raw data and documents to deployed models and decision-support tools.
I design and implement data pipelines, machine learning models, and AI agents that work with real-world constraints: noisy data, incomplete documentation, compliance rules, and human-in-the-loop workflows. My recent work includes document intelligence systems using transformers, RAG-based knowledge agents, Spark-based data pipelines, and ML workflows designed for reliability and traceability rather than demos.
I have a background in large-scale construction projects, which strongly influences how I build AI: clear logic, auditable outputs, and systems that must hold up under regulatory and operational scrutiny.
I’m comfortable owning projects end-to-end — scoping, implementation, documentation, and handover.
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