I specialise in both front-end and back-end engineering — I like making the UI look clean, responsive, and accessible, but I also care a lot about what happens behind the scenes. On the back-end side I work with C# and Python to build modular services with clean contracts, proper validation, and observability. On the front-end side I’m comfortable with HTML, CSS, and modern JavaScript, building responsive pages and admin-style dashboards that talk to REST APIs.
I am currently studying Computer Science at Manchester Metropolitan University and I’m a prospective 2026 graduate, so most of my work is aligned with real coursework briefs — data structures & algorithms, web development, AI coursework, and networking. I try to build things the way industry would expect: small PRs, good commit messages, documented endpoints, and testable code. I also support other students as a lab demonstrator, so I explain concepts clearly and write code that other people can follow.
I’m comfortable across AWS/Azure, Docker, REST/JSON, and event-driven patterns, and I’ve also built uni-style projects that integrate with tools like Firebase for auth and storage. Recently I’ve been prototyping agentic / tool-using flows (plan → call tools → retry) to automate repetitive migration or reconciliation steps. I care about code that is secure, logged, and observable because I’ve done student-engagement and community roles where reliability actually mattered.
To support more data-heavy and fintech-style platforms, I’ve also been working with patterns like ETL for structured and semi-structured data, API-based ingestion of public/financial sources, and surfacing those into reporting / visualisation dashboards (React + charts) so that decision makers can see fresh data. This sits nicely with my AI interests — I can plug in Python/scikit-learn style predictive models or LLM-based enrichment on top of the collected data, which is the same direction that investment and venture-capital platforms are going towards.