Axon console — graph view
Axon
Multi-agent system that aligns corporate ideas into a Neo4j knowledge graph. LangGraph orchestration, FastAPI backbone, React console.
LangGraph · Neo4j · FastAPI Case study →
Carlos Ruiz
builds intelligent systems
that ship.
Systems engineer working at the intersection of AI, full-stack, and cloud infrastructure. I design and operate the entire stack — from LangGraph agents to Kubernetes clusters running them in production.
Focus Agent systems
Based Managua, Nicaragua
Status Open to work
Experience 4+ years
01 Capabilities
An end-to-end engineer.
Most teams need someone who can move fluidly between agent logic, frontend polish, and the infrastructure underneath. That's the gap I close.
01
AI & agent orchestration
Production agent systems built on LangChain and LangGraph. State machines, tool calling, evaluation harnesses, retrieval pipelines.
02
API & backend services
Typed FastAPI and Django services with clean domain boundaries. Async workers, background jobs, observable by default.
03
Frontend systems
Modern React applications. Component libraries, accessible primitives, performance budgets respected.
04
Infra, DevOps & MLOps
Containerised everything. Kubernetes for stateful workloads, Serverless for spiky ones. Repeatable, observable pipelines.
02 Hero project
Axon — turning ideas into a graph.
03 Projects
Selected work.
A small set of recent systems where the architecture mattered more than the framing copy.
04 Cloud & Ops
Versatile across the three.
I match the cloud to the problem rather than the other way around. Production experience on each, with a strong preference for portable infrastructure.
AWS
AWS
Primary
EKSCompute
LambdaCompute
RDS · AuroraData
SageMakerML
BedrockAI
CloudFront · S3Edge
AZ
Azure
Enterprise
AKSCompute
FunctionsCompute
Cosmos DBData
OpenAI ServiceAI
AI FoundryML
Front DoorEdge
GCP
Google Cloud
Data & AI
GKECompute
Cloud RunCompute
BigQueryData
Vertex AIAI
Pub/SubEvents
Cloud CDNEdge
05 Next steps