Selected work
Case studies from my work (client names kept private) and personal projects around cloud, platform engineering and AI tooling.
Designed and implemented an enterprise data platform spanning Azure and GCP for a global banking company, fully provisioned with IaC and delivered through automated pipelines.
~80% better data quality · ~70% stronger data security
Containerised a microservices web application and deployed it to Azure Kubernetes Service, with Azure DevOps for CI and Argo CD for continuous delivery.
Higher scalability, much shorter deployment times
Owned the CI/CD pipelines for a microservices application on AKS, using Azure DevOps and GitHub Actions to automate testing, deployment and monitoring.
Fully automated test → deploy → monitor flow
Brought existing, hand-built cloud environments under Terraform and Terragrunt, with plan/apply pipelines and Terratest checks.
Personal site and blog built with Astro 7, Tailwind CSS 4 and Markdown content collections, with dark mode, RSS, a sitemap and no client-side framework. Deployed on Cloudflare Pages.
Experiments, modules, scripts and the occasional half-finished idea.
Write-ups are part of the portfolio too.
I work on several projects at once. This is the harness loop I built around my coding agents (worktrees, tickets as a dependency graph, and a cleanup step), and how it evolved from a shell alias into something I trust.
What I set up (and agree on with the team) before anyone installs Argo CD. Spoiler: most of it is conventions, not tools.
Everyone wants an AI agent in their pipeline. Here's where I've seen them pay off, where they cause trouble, and the setup I suggest to keep them out of production.