Summary
Alexsander Hamir is a Performance Engineer with a decade of hands-on experience optimizing low-latency, high-throughput systems from the Bay Area. He specializes in pragmatic profiling and caching fixes—often called in when scaling by adding servers isn't the right answer—and has a track record of cutting cache misses and raising throughput in production. His open-source work includes tools that automate and accelerate performance analysis (Prof, Prof AI, Auto Prof) and higher-performance pooling and concurrent-system simulators (GenPool, GoFlow), often delivering double-digit improvements in throughput or efficiency. He’s comfortable across Go, Rust, Python, and TypeScript and has built both developer tooling and user-facing systems, from LLM proxies to payment portals that processed six-figure volumes. A self-taught computer scientist who runs experiments quickly, he brings startup speed and owner mentality—he even architected daycare fintech and operational systems to solve real-world problems during COVID. Not obvious at first glance: he blends systems-level tuning with agentic automation, turning repetitive profiling tasks into autonomous workflows that save teams hours.
10 years of coding experience
3 years of employment as a software developer
Computer Science, Computer Science at Self-taught
Portuguese, English