Senior Engineering Manager · MSI Data
I build the platforms engineering teams ship on.
Cloud infrastructure, DevOps and platform engineering on AWS — and the teams behind them. Eight years turning fragile systems into reliable ones, and manual releases into pipelines people trust. Based in Wisconsin.
Selected impact
Outcomes from production systems, not side projects.
Experience
From data pipelines, to cloud architecture, to leading the engineers who own both.
Senior Engineering Manager
MSI Data · Wisconsin
- Leading engineering delivery across cloud infrastructure, platform and application teams.
- Responsible for 11 engineers, having grown the organisation from 2 reports to 4 and then to its current scope.
- Owning technical direction, architecture decisions and the health of the systems behind them.
- Growing engineers through mentoring, review practice and clear operational standards.
DevOps / Cloud Manager
MSI Data
- Owned AWS infrastructure end to end — provisioning secure, reliable environments and setting cloud and DevOps strategy.
- Directed design and operation of CI/CD pipelines, automating provisioning and deployment for consistency across environments.
- Led a full-cycle redesign of microservices infrastructure, improving EC2 performance within EKS.
- Introduced monitoring that sustained 99.9% availability while cutting third-party tooling costs.
- Translated stakeholder requirements into architecture, then delivered it with small cross-functional teams.
Data Analyst (Contract)
CDC Foundation
- Designed and maintained ETL pipelines and data architectures, optimising for quality and reliability.
- Built the COVID-19 warehouse inventory reporting pipeline and visualisations, generating $30K+ in monthly savings.
- Delivered analytics and BI solutions that measurably shortened decision-making cycles.
Data Analyst / Python Developer
Delta Defense
- Architected and evolved four data pipelines processing terabyte-scale datasets in real time.
- Led full-stack design and delivery of 12 cloud-based applications.
- Built a lead-tracking application that reduced customer churn.
Building with AI, carefully
Personal projects, built on my own time and infrastructure. I'm less interested in what AI can generate than in what it can be trusted to do unsupervised — and in the controls that make the difference.
A governed multi-agent research system
Python · GitHub Actions · Claude Code agents · 128 commits
- Six specialist AI agents that hand work to each other through a deterministic orchestrator, rather than a human re-prompting at every step.
- Enforcement in code, not prompts: 26 validator modules and 149 automated tests across 19 CI workflows. Agents cannot approve their own output, edit the rules that govern them, or push to protected branches.
- Every decision an agent makes must cite the rule it relied on, and the citation is machine-checked against the agent's own write-up — so an agent can't pad a rule list or lean on a rule it never declared.
- Caught and documented real failures rather than hiding them: a misattributed citation that passed an identifier-only check, an agent's flawed statistical argument, and a case where my own summary over-claimed a result the evidence contradicted.
- The point isn't output volume. The system's two completed investigations both ended in a documented stop — one because a 28,000-participant meta-analysis had already answered the question the other way. Knowing when to stop is the hard part.
An AI engineering assistant with persistent memory
Python · local TTS · WSL and macOS
- A always-on assistant with local voice synthesis, lip-synced visual presence, and notes that survive between sessions — so context isn't re-explained every morning.
- Hook-driven automation wired into the development environment: session startup, interrupt handling, global hotkeys, and a meeting transcription path that runs entirely on local models.
- Portable across WSL and macOS, with platform-specific paths isolated behind fallbacks.
Capabilities
What I reach for, and what I've run in production.
Cloud & Infrastructure
AWS (EC2, EKS, RDS, S3, CloudFront, Route 53), Google Cloud, infrastructure as code, cost and capacity management.
Containers & Orchestration
Kubernetes, Docker, EKS, purpose-built build containers, microservices architecture.
CI/CD & Automation
GitHub Actions, GitLab CI, Jenkins, automated provisioning and deployment, release engineering.
Languages
Python, SQL, Bash, PowerShell, R.
Data & Analytics
ETL pipeline design, MySQL, PostgreSQL, T-SQL, Looker, Domo, Tableau, Sumo Logic.
Leadership
Engineering management, cross-functional delivery, stakeholder and vendor management, mentoring, operational standards.
Education & certification
Engineering foundations, plus a science degree that keeps the analytical side sharp.
MS, Applied Biotechnology
University of Wisconsin–Oshkosh · December 2024
BS, Software Engineering
Southern New Hampshire University · May 2021
AWS Certified Cloud Practitioner
Amazon Web Services
Get in touch
Happy to talk cloud platforms, engineering leadership, or building with AI.