Software architecture and modernisation
Support with .NET services, APIs, maintainability, integration boundaries, legacy process analysis and pragmatic modernisation planning.
some · bright · minds · create · new · thoughts
Architecting intelligent software. Engineering real-world impact.
I help teams explore, design and deliver software systems that are maintainable, scalable and grounded in real-world needs, from .NET services and event-driven platforms to applied AI prototypes and bioacoustic machine learning.
10+ years
software engineering experience
Applied AI
bespoke agents, local AI and applied machine learning
Strategic transformations
systems and workflow modernisation
AI recognition
BCSWomen Lovelace Colloquium MSc Honourable Mention
What I can help with
Support for organisations undergoing technical transformations and technical support for teams exploring software, systems and AI.
I work best where software engineering discipline meets emerging technology: turning ideas into clear options, prototypes and maintainable systems.
AI integration and prototyping
Practical exploration of AI-assisted workflows, local model orchestration, retrieval systems, data pipelines and proof-of-concept delivery.
Event-driven and distributed systems
Design thinking around messaging, asynchronous workflows, observability, integration pipelines and scalable backend services.
Technical transformations
Strategy, planning and adoption: identifying realistic opportunities, shaping delivery options and translating complex technology into usable change.
Technical and AI transformation
Bridging strategy, systems and practical AI adoption.
AI transformation is not only a tooling question. It also needs clear goals, process awareness, leadership, communication and an honest understanding of where technology can create value without creating unnecessary risk.
I help teams bridge the gap between technical possibility and practical adoption: identifying realistic AI opportunities, shaping delivery options, modernising workflows and translating complex technology into usable change.
The aim is to create transformation that is useful, maintainable and trusted, not just to introduce new tools. That means looking at systems, people, data, risk, integration points and the day-to-day reality of how work actually happens.
How I can support transformation work
Bespoke AI agents
Atticus as a model for private, useful and deeply personal AI systems.
Atticus is my local AI study companion and research assistant: a privacy-first system that runs on my own hardware, routes tasks between specialist models and uses local memory to support postgraduate study, technical reasoning and scientific exploration.
The same principles can be applied to bespoke agents for individuals or teams: assistants that understand your documents, workflows, systems and preferred ways of working, without forcing sensitive data into generic cloud tools.
What a bespoke agent can support
Approach
Clear thinking before code, careful engineering after it.
My background combines hands-on senior engineering with independent applied AI projects and ongoing professional development in artificial intelligence. I can help with early technical discovery, system design, prototype shaping and implementation support.
I prefer practical, explainable technology choices over novelty for its own sake. The goal is to make systems easier to understand, easier to operate and easier to evolve.
The phrase in the opening line reflects how I approach AI as a toolbox rather than a single catch-all solution. Search, probabilistic models, Markov processes, classifiers, neural networks and transformer-based systems each suit different kinds of problems and rely on different underlying algorithms. The important part is choosing the right method for the context, then engineering it into something useful, maintainable and trustworthy.
Core technologies and themes
AI from first principles
Understanding the algorithms beneath the tools.
I approach AI as an engineering discipline, not just a collection of APIs or model names. My work combines professional software engineering with postgraduate study in artificial intelligence, strengthening the algorithmic foundations behind practical AI systems: how problems are represented, how models learn from data, how uncertainty is handled and how performance is evaluated on unseen examples.
Search and optimisation
Representing problems as states, actions and goals, then selecting efficient strategies for exploring possible solutions.
Probabilistic reasoning
Using probability, conditional independence and Bayesian thinking to reason under uncertainty and support explainable decisions.
Supervised learning
Building classifiers from labelled data, including feature representation, model training, validation and prediction on unseen inputs.
Evaluation and generalisation
Assessing whether a model is genuinely useful beyond its training data, with attention to overfitting, bias, metrics and real-world consequences.
Selected work
Distinctive technical projects with real-world context.
Bioacoustic Health Monitoring
A Raspberry Pi and PyTorch-based proof of concept for detecting signs of respiratory illness in hedgehogs through spectrogram-based audio analysis.
View portfolio projectAtticus.ai
A local AI study companion using multiple local models, semantic routing, FAISS memory and privacy-first research workflows, now informing my approach to bespoke AI agent design.
View portfolio projectEvent-driven engineering
Professional experience across .NET APIs, Azure Service Bus, Kafka, Pub/Sub, CI/CD and integration-heavy enterprise systems.
View experienceAbout me
Engineer, AI solutions specialist, maker and conservation-minded technologist.
I’m based in the North East of the UK, with a background spanning supply chain technology, finance, transport systems, IoT platforms and AI-enabled products.
Alongside professional engineering work, I enjoy the great outdoors, wildlife conservation and building AI projects that connect back to real-world contexts, whether that’s a local study assistant or a Raspberry Pi-based wildlife monitor.
A lot of my work is driven by curiosity and purpose. I’m especially interested in technology that is useful, understandable and respectful of privacy, whether that means distributed systems for businesses or small bespoke AI systems.
Recognition
Applied AI recognised at the BCSWomen Lovelace Colloquium.
My bioacoustic hedgehog health monitoring project was recognised with an Honourable Mention in the MSc category at the 19th BCSWomen Lovelace Colloquium. The project explores localised AI, audio processing and edge computing for non-invasive wildlife health monitoring.
Get in touch
Have a project, idea or technical problem worth exploring?
I’m open to selected consultancy conversations, collaborations and professional opportunities where software engineering and practical AI can create meaningful value.
Whether you need an AI opportunity review, a local agent prototype, a legacy workflow modernisation assessment or an engineering architecture review, I can help you move from possibility to practical delivery.