Software Engineer · Cloud Architect

I build reliable software
that scales quietly.

I help teams ship faster by migrating workloads to the cloud, automating the parts that should never be done by hand, and turning one-at-a-time processes into systems that run by the hundred.

01

About

I'm a software engineer focused on the unglamorous parts of building software: making it run, keeping it running, and making sure the next person to touch it doesn't dread it.

I've worked across cloud migrations, infrastructure automation, and backend systems — including production work for a Fortune 500 company. I care about pragmatic engineering: solving the real problem, measuring the result, and removing toil rather than adding tooling.

Currently open to staff/principal AI engineering roles.

  • $100k+ Annual savings from one automation project at a Fortune 500
  • 100× Throughput increase by parallelizing a sequential workflow
  • 0 → Azure Migrated a fragile single-server app to a managed cloud footprint
02

Selected work

Three projects I keep coming back to in interviews — each one was a quiet, measurable win.

Cloud infrastructure illustration
Case study 01 · Cloud migration

From a shoestring server to managed Azure

Problem

A revenue-generating web app was running on a single under-provisioned server with no redundancy. Outages were frequent and there was no path to scale.

Approach

Rearchitected the app for Microsoft Azure — managed app service, managed database, CDN in front of static assets, infrastructure defined as code so it could be rebuilt from scratch.

Impact

Cut response times, made the system reliably available, and made future changes safe to ship because nothing was hand-configured anymore.

  • Azure
  • App Service
  • Infrastructure as Code
  • CDN
Automation illustration
Case study 02 · Automation

A six-figure-per-year scripting win

Problem

A Fortune 500 team was manually configuring single-board computers as part of a recurring deployment workflow. It was slow, error-prone, and the cost compounded across hundreds of devices.

Approach

Reverse-engineered the manual steps, turned them into a repeatable script that handled the full provisioning lifecycle, and built in verification so failures surfaced immediately instead of weeks later in the field.

Impact

Saved over $100,000 per year in labor, eliminated a long tail of human-error defects, and freed the team to work on higher-leverage problems.

  • Embedded systems
  • Serial console automation
  • Scripting
  • Hardware provisioning
Parallel processing illustration
Case study 03 · Scale

From one-at-a-time to hundreds in parallel

Problem

An automated process could only run a single job at a time. As demand grew, the queue grew with it, and the only knob anyone could turn was “wait longer.”

Approach

Restructured the workflow so each job was independent and idempotent, moved coordination off the host, and added concurrency controls so we could safely run hundreds of jobs simultaneously without stepping on shared resources.

Impact

Throughput went up roughly two orders of magnitude, backlog dropped to near zero, and the team got back the engineering hours they were spending babysitting the queue.

  • Concurrency
  • Queueing
  • Idempotency
03

Skills

The tools I reach for — trim to taste.

AI & LLMs

  • LLM integration (Azure OpenAI, GPT-4 in production)
  • Agentic pipelines (Playwright, Container Apps)
  • Claude Code, Cursor (daily driver)
  • Ollama, LM Studio (local models)
  • Prompt design and eval

Languages

  • TypeScript / JavaScript
  • C# / .NET / .NET Core
  • Python
  • SQL

Cloud & systems

  • Azure (Functions, Container Apps, Service Bus)
  • Distributed systems and microservices
  • CI/CD and infrastructure as code
  • Containers

Frontend

  • React
  • ASP.NET MVC
  • Component architecture and modernization
04

Get in touch

The fastest way to reach me is email. I respond within a day or two.