Granite
Tait
Site Reliability Engineer
AI Hackathon Winner
Two-time AI hackathon winner, Kubernetes and DevOps expert, and triathlete based in Utah. At Nusano I architect the platform behind a linear particle accelerator with Kubernetes, Terraform, Argo CD and GitOps: redundant by design, built for uptime.
Site reliability engineer & platform architect
Nusano makes radioisotopes with a linear particle accelerator. I design, build and run the platform under it at all three sites: Kubernetes and Argo CD, with Terraform and Ansible underneath.
- Kubernetes
- Argo CD
- Terraform
- Ansible
- Grafana
279
Minutes per deploy, across 12 appsNobody asked me to fix it. I designed, built and shipped the new pipeline on my own, with instant rollbacks.
I owned the deploy pipelines for 20+ microservices end to end: standing up new ones, rescuing broken ones and retiring old ones.
- Dev
- QA
- Staging
- Production
- Azure DevOps
- TeamCity
- Octopus Deploy
- PowerShell
- Python
AI
hackathons
Two wins and a finalist, at some of the biggest AI competitions in Utah.
Winner · Podium AI HackathonAIMy
A voice kiosk for retail. Say what you need, hear product picks, take the list with you by QR code.
Code ↗
Winner · DAVID AI Hackathon · $1,000Swarmy
Turns a product idea into a crowd of synthetic users and runs the research before you build.
swarmy.buzz ↗
Finalist · Utah Tech Week HackathonQuorum
A board of AI agents (CFO, CMO, CTO and legal counsel) that debate your business decisions and hand back one recommendation. I pitched it on stage at Utah Tech Week.
Code ↗Experience
9 years, one direction: closer to the systems that have to stay up.
- 2026–nowNusano
Site reliability engineer and platform architect. Kubernetes, Argo CD and Terraform across three sites.
- 2025–26Alpha Warranty
Senior QA. The pipeline, and AI bug triage that cut duplicates 70%.
- 2022–25Paycor
DevOps for 100+ developers: 20+ microservices, hundreds of deploys a week.
- 2022Ascend Staffing
Traveling sysadmin. Up to 30 tickets a day.
- 2017–20BYU
Ran a molten-salt simulation lab and a team of 7–8 students.
Co-author, J. Phys. Chem. B (2021), on molybdenum in molten salt.
English, and Japanese at full professional proficiency.
Writing
Notes from production: AI tooling, pipelines, and what broke along the way.
Building Maestro: What I Learned Automating My Mornings with AI
How I built a multi-agent system that pulls your calendar, weather, Strava data, and priorities while you sleep — and why the hardest part wasn't the AI.
Read →RAG Pipelines in Production: What I Learned the Hard Way
The real-world challenges of running RAG in production: chunking strategies, embedding model drift, and the vector database gotchas I learned the hard way.
Read →Automating Bug Root-Cause Analysis with Git Blame and GPT-4o
How I built a system that automatically traces bugs to the commits that introduced them — turning 'who broke this?' from a blame game into an automated answer.
Read →