I build full-stack AI products, retrieval systems and visual interfaces that make complex information easier to understand across legal technology, public services and other high-stakes domains.
Projects at the intersection of AI engineering, visual analytics, legal technology and responsible system design.
An AI-assisted employment-law triage and recommendation system combining conversational context gathering, curated legal data, RAG and interactive explanations of possible dispute-resolution pathways.
A reusable legal-process explorer combining semantic and keyword flow selection, graph validation, explainable pathways and regression testing across administrative-justice templates.
A privacy-policy analysis assistant that retrieves relevant clauses, surfaces provenance-aware snippets and presents confidence and risk signals for human review.
Interactive refugee-movement narratives, geospatial data experiences and WebXR prototypes that turn complex datasets into explorable stories and spatial insight.
I work across the product stack while remaining attentive to evidence, usability, regulation and real-world deployment constraints.
React and TypeScript interfaces, Python/FastAPI and Node.js services, REST APIs, relational data models, testing and iterative delivery.
Curated knowledge, vector search, classification, LLM orchestration, provenance, evaluation and human-in-the-loop system design.
Visual pathways, plain-language interaction, responsible AI, stakeholder co-design and technology for access to justice.
I am an applied AI and full-stack engineer, legal-tech researcher and product founder based in the United Kingdom. My PhD research at Bangor University examines how AI, visual representation and knowledge structures can help people understand legal processes and digital justice pathways.
My experience spans software engineering, data science, medical imaging, human-computer interaction, teaching and cross-disciplinary research. I am most valuable where technical depth must be combined with careful communication, user evidence and responsible delivery.
A focused view of the roles most relevant to senior software, applied AI and legal-tech opportunities.
Researching AI-assisted legal guidance, knowledge representations, RAG and visual interfaces that make legal pathways more transparent and navigable.
Led the technical development of EmployODR, including the React interface, OpenAI integration, RAG workflow, legal classification and iterative expert testing.
Lead product strategy, software delivery, business development and stakeholder relationships while remaining hands-on with technical innovation.
Teach practical Machine Learning, Advanced Machine Learning, Information Visualisation and Creative Visualisation sessions to undergraduate and postgraduate students.
Developed a Python framework combining rigid registration, deep neural networks, preprocessing and quantitative evaluation for 3D medical-image alignment.
I am interested in remote senior software engineering, applied AI, ML/data engineering and legal-tech opportunities where I can contribute during my PhD and continue growing with the team.