Available for new work
Senior full-stack engineer with 7+ years shipping production SaaS — AI agents and LLM workflows, the APIs behind them, and the interfaces that make them usable.
What I do
Most products stall at the seams between these. I work across all four, so the seams are designed rather than discovered.
React and Next.js applications where the hard part is the data — analytics dashboards, AI-generated content review, and admin surfaces that stay quick as the payload grows.
Python and Node services built to carry AI workloads: typed REST and GraphQL contracts, async processing and queues, hardened auth, and observability wired in from the first deploy.
Content and commerce platforms the owning team can actually run — WordPress and Shopify builds, headless architectures, and content models designed so routine changes never reach an engineer.
LLM workflows that behave predictably in production: prompt frameworks, agent design with tools and memory, retrieval over vector stores, and the evaluation loop that keeps quality measurable.
Selected work
A few projects that show the range — with the outcome, not just the stack.
Led end-to-end development of review-response agents on OpenAI and Claude, with tool integrations and memory for autonomous operation — and a prompt framework that cut model cost 18%.
Resilient integrations with Google Business Profile, Yelp and Facebook Reviews — webhook-driven where the platform allows it, scheduled where it doesn't, reconciled either way.
A multi-locale marketing site moved onto a Next.js frontend with WordPress as the editing layer — including the preview and publishing pieces that headless builds usually drop.
React and Next.js dashboards surfacing AI metrics and generated responses for client decision-making — increasing engagement 28% by making the model's work inspectable rather than opaque.
Experience
Jan 2024 — Apr 2026
Led end-to-end AI agent development for review-response workflows on OpenAI and Claude, integrating tools and memory for autonomous operation. Built the prompt-engineering framework that raised response reliability while cutting model cost by 18%, and kept integrations with Google Business Profile, Yelp and Facebook Reviews at 99.9% data-sync uptime.
Oct 2022 — Dec 2023
Built cloud-native Python and Node services exposing REST and GraphQL APIs for AI workloads and partner integrations. Dockerised CI/CD onto Kubernetes accelerated release cycles by 40%, and redesigned SQL/NoSQL data models doubled pipeline throughput. Mentored engineers and introduced the testing strategy.
Apr 2021 — Oct 2022
Architected backend microservices supporting AI workflows behind secure REST and GraphQL APIs, and built the React/Next.js dashboards that made AI metrics legible to clients — increasing engagement by 28%. Webhook-based review sync with retry logic held 99.8% data freshness.
Jun 2019 — Feb 2021
Full-stack SaaS development in Python and Node: scalable REST APIs over a service-oriented architecture, data pipelines across SQL and NoSQL, and authentication and authorisation across microservices. Observability and proactive incident response held 99.95% uptime.
Writing
Nobody decides to send 400kB of JavaScript to a phone on a train. It arrives one reasonable-looking import at a time, and the only way to stop it is to make the cost visible.
Frontend4 min read
Retries are not an edge case — they are the normal operating condition of any network. Designing for them turns a whole category of duplicate-record bugs into something that cannot happen.
Backend4 min read
Most confusion about RSC comes from thinking of it as rendering. It's closer to serialisation — and once you see it that way, the rules stop feeling arbitrary.
Frontend3 min read
I'm open to senior engineering roles, contract work, and anything that puts LLMs in front of real users. Tell me what you're working on.