Professional Overview
I build practical AI systems that actually work in the real world. Over the past few years, I’ve focused on designing LLM-driven workflows, agent-style task systems, and multimodal AI integrations that turn generative models into usable tools — not just demos. I work across OpenAI, Anthropic, and Google ecosystems, building structured prompt frameworks, multi-step reasoning flows, and lightweight AI-powered applications using platforms like Gemini and Replit. Before moving deeply into AI, I spent 15+ years leading large-scale, data-driven political operations. That experience taught me how to think in systems, manage complexity, operate under pressure, and build processes that scale. I bring that same discipline to AI — focusing on structure, reliability, governance, and real-world integration. I’m especially interested in applied AI roles where I can design workflows, build agentic systems, and help teams move from “experimenting with AI” to actually shipping value.
Areas of Expertise
AI & Machine Learning Engineers
Design, train, and ship production ML models — from data pipelines to model inference at scale. Covers supervised learning, neural networks, LLM integration, and model optimisation.
AI Product & Strategy
Translate AI capabilities into product roadmaps, define success metrics, and drive adoption across engineering and business teams.
