Staff Software Engineer owns entire product areas end-to-end at an AI evaluation platform, designing full-stack systems, making high-stakes technical decisions, shipping features, and driving measurable impact. Requires 8+ years experience with deep technical expertise in web apps and product judgment.
Salary not listed
Hybrid8+ YOEFullstack Engineering
About the role
Responsibilities
Own product areas end-to-end — from identifying opportunities that aren't on anyone's roadmap, to building conviction, shipping, and driving to measurable outcomes
Design complete systems: data model, API design, frontend architecture (full-stack) or backend services and infrastructure (backend), and deployment strategy
Make high-stakes technical decisions under uncertainty — build-vs-buy, monolith-vs-service, when to prototype and when to harden — and be accountable for the outcomes
Work with ML researchers to turn research services into reliable, product-consumable systems
Ship and iterate — measure, course-correct, and drive to sustained impact
Raise the technical and product quality bar on the team — introduce practices others adopt, unblock teammates, and create clarity out of ambiguity
Navigate cross-functional collaboration with product, design, research, and leadership to align on what matters
Requirements
8+ years of experience in software engineering, with a focus on product development
Deep experience building web applications spanning data model, API, frontend architecture, and deployment
Track record of repeated, attributable impact — multiple projects across different roles or companies where you can quantify outcomes (revenue, engagement, efficiency)
Personal technical depth: dealt with real performance issues: slow queries, N+1 problems, caching, transaction isolation
Product judgment and autonomous ownership — identified opportunities, validated them with evidence, built buy-in, shipped
Clear, persuasive communication — build buy-in across engineering, product, and leadership
Genuine conviction about AI evaluation and Arena's mission
Nice-to-Haves
Production experience with AI/LLM systems — inference pipelines, evaluation workflows, model integration, or AI-powered product features
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