Site Reliability Engineer

ABOUT ARENA INTELLIGENCE Arena is the platform for evaluating how AI models perform in the real world. Founded by researchers from UC Berkeley's SkyLab, we're on a mission to measure and advance the frontier of AI for real-world use, and to build the foundation for everyone to understand, shape, and benefit from it. Tens of millions of people use Arena each month to evaluate how frontier systems handle the work they actually do. The preferences they share power the most transparent, rigorous, and human-centered evaluations in AI. Leading AI labs, enterprises, and independent researchers rely on our work and open datasets to understand how models behave in real workflows: agentic coding, creative generation, professional productivity, and beyond. We go beyond leaderboards and decompose what human experience reveals about AI, so models advance toward the work people actually do. We're a team of researchers, academics, builders, and creatives from UC Berkeley, Google, Stanford, and DeepMind. We seek truth, move fast, and value craftsmanship, curiosity, and impact over hierarchy. We're building a company where thoughtful, curious people from all backgrounds can do their best work together, in an office culture that radiates excellence, energy, and focus. ABOUT THE ROLE Arena Intelligence is looking for an engineer to build the core infrastructure that sits beneath our online evaluation systems — the AI gateways, automated arena runtimes, and serving layers that make real-world model evaluation possible at scale. This is a critical part of the Arena Service. Arenas are live, online systems: they route traffic across frontier models from many providers, handle bursty and unpredictable load, need to fail gracefully when upstream models do, and have to remain fair and consistent under all of it. We exist to build foundational infrastructure for our users that scales, is reliable, and makes the complexities of operating this infrastructure at scale disappear. We need a pract