// Background
A career arc built at the intersection of platform reliability and AI.
I've spent my career inside environments where downtime is measured in real consequences — regulated financial platforms, mission-critical manufacturing systems, and early-stage products scaling from zero. The through-line is reliability.
// Career timeline
Wells Fargo Advisors
Sr. SRE / Tech Lead
Keeping advisor-facing platforms running in a regulated hybrid-cloud environment.
Led site reliability engineering for high-availability platforms serving 15,000+ advisors. Owned SLO design, incident management, observability, and infrastructure reliability in an environment where compliance and uptime are non-negotiable.
General Motors
Sr. Cloud Platform & Reliability Engineer
Mission-critical engineering platforms and production AI systems.
Built and operated mission-critical engineering platforms with AKS, Terraform, Python, and PowerShell automation, plus HPC server management for CFD and wind-tunnel data pipelines. Also built production AI systems — multi-agent orchestration (LangGraph) and RAG — under the same reliability discipline.
iCone
Early Engineer — Employee #2
Built from nothing. Now powers Waze, Google Maps, and AV manufacturers.
Joined at the very beginning and helped take the platform from zero to production scale. The platform now underpins Waze, Google Maps, and AV manufacturers.
// Academic credential
M.S. in Artificial Intelligence / Machine Learning
Formal grounding in modern AI/ML — applied directly to production work, including RAG prototyping for incident analysis and reliability engineering for AI-native systems. Not a credential for credibility's sake; it closes the loop between platform reliability and AI systems.
Why it matters
Most platform engineers with senior enterprise experience don't have this. Most AI engineers don't have the platform experience. The combination is the defensible position.
// The position
The combination of M.S. AI/ML credentials, enterprise SRE experience at regulated institutions, and production AI deployment is rare in a single person. That's not a claim — it's a verifiable career record.