Software Architect — distributed systems & scalable design

I design systems for scale, then make sure they don't fall over.

I work on service boundaries, failure modes, and the trade-offs between consistency and availability — the decisions that determine whether a system survives its own success.

DESIGN SCALE RESILIENCE

About

I spend most of my time upstream of the code — drawing service boundaries, mapping data flow, and reasoning about what happens when a dependency goes down at 3am. The implementation matters less than whether the architecture holds under load.

That means thinking in terms of consistency models, failure domains, and blast radius before a single endpoint gets written — then leaning on AI tooling to accelerate the build once the design is sound.

  • Architecture Event-driven
  • Scaling Horizontal
  • Consistency Eventual
  • Resilience Circuit breakers
  • Observability Metrics & tracing

Focus

Stop 01

Distributed Systems Design

Defining service boundaries and API contracts, choosing between synchronous and event-driven communication, and designing for partial failure from the start.

Service boundaries Event-driven
Stop 02

Scalability & Performance

Capacity planning, horizontal scaling, and caching strategy — designing systems that degrade gracefully instead of falling over under load.

Load balancing Caching
Stop 03

Reliability & Observability

Fault tolerance, graceful degradation, and instrumentation that tells you what actually broke — SLOs, tracing, and clear failure domains.

Fault tolerance SLOs

Now

Working through the trade-offs between strong and eventual consistency for a system currently split across too many single points of failure — mapping out where to introduce a message queue versus where it'd just add latency for no reason.