Runtime engineering
C1/C2, inlining, escape analysis, deoptimisation, safepoints and generated-code verification.
Principal JVM Performance Engineer
Building predictable systems beneath the framework layer.
I design and optimise latency-sensitive financial platforms, JVM runtimes and event-driven systems. My work spans architecture, JIT behaviour, memory allocation, concurrency, CPU caches and the operating system beneath the convenient abstractions.
10×+faster payment workload
75%lower memory footprint
90%lower infrastructure cost
10+ yrsfinancial and runtime systems
Engineering domains
Performance across the execution stack
The fastest code is rarely produced by staring harder at a service method. Architecture, ownership, allocation and hardware behaviour have an irritating habit of mattering.
Concurrency
VarHandles, acquire/release, SPSC/MPSC structures, lock contention and cache coherence.
Memory
Allocation elimination, FFM, MemorySegment, fixed layouts and deterministic lifetimes.
Systems
Linux perf, NUMA, CPU affinity, ARM/x86, UDP, QUIC, shared memory and Rust.
Interactive learning
Performance Lab
Small visual models for concepts that are usually explained with three paragraphs, a dubious analogy and avoidable suffering.
Selected work
Engineering case studies
Sanitised examples built around problem, evidence, design and result. No confidential internals and no miraculous benchmark folklore.
30–50 seconds to ~4 seconds
Parallel execution, allocation control and a 75% reduction in memory use.
Replacing synchronized contention
Lock-free, near zero-allocation infrastructure for a high-volume platform.
Database-bound to CPU-bound
In-memory computation reduced latency and infrastructure expenditure.
Guided curriculum
Performance Academy
A structured route from measurement fundamentals to runtime architecture. Not a “become principal in fourteen days” funnel. The universe has enough of those.