Job Summary:
Arena Intelligence is an innovative company focused on AI model evaluation, born out of UC Berkeley’s SkyLab. The Infrastructure Engineer will own core infrastructure, build API-based products, and collaborate with founders and early customers to define and develop enterprise-grade solutions.
Responsibilities:
• Build API based products from the ground up.
• Design and implement a low-latency, high-reliability APIs for leaderboards, models, and arenas.
• Solve hard streaming problems.
• Handle SSE/streaming responses across heterogeneous providers, including partial failure recovery, mid-stream fallback, and consistent response normalization.
• Ship enterprise-grade infrastructure.
• Build the systems enterprise customers expect: rate limiting, authentication, usage metering, cost attribution, audit logging, and SOC2 compliance.
• Build deep observability.
• Instrument infrastructure with distributed tracing, latency breakdowns, token-level usage tracking, and real-time dashboards so customers (and we) can see exactly what’s happening.
• Build AI centered products.
• Integrate with our core evaluation platform, Arena data, and customer-specific benchmarks.
• Collaborate with the research team to turn novel ideas into full-featured products.
• Flex across the stack.
• Contribute to the backend of our Leaderboards and Evals platforms when needed, helping unify our public and private data architectures.
Qualifications:
Required:
• 4+ years of backend engineering experience, with meaningful time spent on distributed systems, infrastructure, or developer-facing platforms.
• Strong proficiency in Go and/or Rust, with hands-on experience building high-throughput APIs or proxy/gateway systems.
• Experience with LLM provider APIs (OpenAI, Anthropic, Google, etc.) and a working understanding of the challenges: streaming, token management, rate limits, model-specific quirks.
• Solid cloud infrastructure skills — you’re comfortable with AWS or GCP, Kubernetes, Terraform, and database systems like Postgres and Redis.
• A product-oriented mindset. You think about the developer experience of your APIs, not just the implementation. You ask 'why' before 'how.'
• Comfort with ambiguity. We’re a startup. Scope is fluid, context shifts, and you’ll wear many hats. That should sound exciting, not stressful.
Preferred:
• Experience building API gateways, proxies, or developer tools (Bifrost, Kong, Envoy, Tyk, or custom).
• Background in ML infrastructure, model serving, or evaluation frameworks.
• Experience building enterprise-ready features: SSO, RBAC, audit logs, multi-tenancy.
• Familiarity with the modern AI infra stack (vLLM, LiteLLM, LangChain, etc.).
Company:
We partner with investors, founders, and ambitious teams at pivotal moments of growth, helping them build the people, talent, and leadership infrastructure required to scale with confidence. Founded in 2023, the company is headquartered in San Francisco, CA, US, , with a team of 2-10 employees. The company is currently Early Stage.