Available for projects

Dillon Browne

Engineering resilient, scalable infrastructure for the AI era — from multi-cloud architecture to production ML pipelines.

24h response Remote & on-site 10+ years
10+ Years
50TB Daily traffic
99.99% Uptime
100+ Services
Stack

Technologies

Kubernetes
Orchestration
500+ node clusters
Terraform
IaC
Multi-cloud scale
AWS
Cloud
Primary platform
GCP
Cloud
GKE & data
Cloudflare
Edge
50TB+ daily
Elasticsearch
Observability
5TB+ logs/day
Go
Language
Cloud-native
LangChain
AI/ML
RAG pipelines
Prometheus
Metrics
At scale
Vault
Security
Secrets mgmt
Metrics

Impact & results

0+
Years of Engineering Excellence
0TB+
Daily Traffic Managed
0TB+
Daily Log Processing
0%
Average Cost Reduction
0%
Uptime Achieved
0+
Deployments Automated Daily
0+
Services Migrated to Cloud
0/7
System Reliability
How it runs

Infrastructure in motion

A live look at the path every workload takes — ingestion, processing, inference, output — across an observable GPU fleet, end to end.

ML Pipeline Flow

Data Ingestion
Processing
Inference
Output

GPU Cluster

Real-time node status

active
loading
idle
Node 1
0%
Node 2
0%
Node 3
0%
Node 4
0%
Node 5
0%
Node 6
0%
Node 7
0%
Node 8
0%
Node 9
0%
Node 10
0%
Node 11
0%
Node 12
0%
Services

Capabilities

Cloud & Infrastructure

  • Cloud migration strategy & execution
  • Multi-cloud architecture design
  • Disaster recovery planning
  • High-availability system design

DevOps & Automation

  • CI/CD pipeline architecture
  • Infrastructure as Code implementation
  • GitOps transformation
  • Development environment standardization

Kubernetes & Containers

  • Kubernetes cluster design & deployment
  • Container orchestration strategy
  • Service mesh implementation
  • Microservices migration

AI/ML Operations

  • LLM infrastructure setup
  • AI agent development & deployment
  • Vector database architecture
  • ML model serving pipelines

Observability & Reliability

  • Monitoring & alerting design
  • Performance optimization
  • Incident response automation
  • SRE practice implementation
Available for projects

Ready to start?

From consultation to full implementation, production-ready solutions tailored to your needs.

FAQ

Frequently asked

What do you do?

I'm a Senior Cloud Architect and DevOps engineer with 10+ years building resilient, scalable infrastructure — multi-cloud architecture (AWS, Azure, GCP), Kubernetes, Infrastructure as Code, observability, security engineering, and increasingly production AI/ML infrastructure (RAG systems, LLM serving, GPU orchestration).

Are you available for work?

Yes. I take on full-time roles and contract engagements, remote or on-site, and typically respond within 24 hours. Use the contact form to start a conversation about your project or role.

What kind of AI infrastructure work do you do?

Production LLM deployments, retrieval-augmented generation (RAG) pipelines, GPU cluster orchestration, vector search, and AI-powered automation — with the same reliability, cost, and observability discipline applied to traditional cloud infrastructure.

How do you approach cost optimization?

Right-sizing, spot/committed-use strategy, autoscaling tuned to real demand, storage-tier and egress review, and continuous FinOps measurement. Past engagements have delivered roughly 40% average infrastructure cost reduction without sacrificing reliability.

How was this website built?

Edge-first: Astro static site with React islands, deployed on Cloudflare Workers with serverless functions, Workers AI for the chat assistant, and KV for rate limiting and caching. Read the full write-up in the "How I Built This" blog post.

What engagement models do you offer?

From advisory and architecture review through to hands-on implementation and operation — cloud migrations, Kubernetes platforms, CI/CD and GitOps, observability, and AI/infrastructure integration, scoped to your needs and outcomes.

Contact

Get in touch

Ready to discuss your next project? Fill out the form below and I'll get back to you within 24 hours.

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Response within 24h

Available