Senior Infrastructure Engineer, Real-Time AI Platform

Arena Intelligence, Inc.; San Francisco (CA); On-site; USD 180,000 - 240,000; Full time

Benefits offered by this job

Competitive compensation

Equity

Health benefits

Transparent culture

Job summary

Arena Intelligence, Inc. is seeking an experienced backend engineer to build the core infrastructure under our online evaluation systems. You will design low-latency APIs for leaderboards and arenas, implement enterprise-grade features, and ensure observability across distributed systems.

You will work with researchers, engineers, and product leadership as an early member of the infra team, navigating zero-to-one challenges and scaling complex workloads in a startup environment.

Qualifications

• 6+ years in backend engineering, distributed systems, or developer-facing platforms.
• Proficiency in Go and/or Rust for high-throughput APIs or gateways.
• Experience with LLM provider APIs and token/rate-limit challenges.
• Cloud infrastructure with AWS or GCP, Kubernetes, Terraform, Postgres/Redis.
• Product mindset focused on developer experience of APIs.

Responsibilities

• Build and orchestrate API-based products from ground up with low latency APIs.
• Ship enterprise-grade infrastructure: rate limiting, auth, usage metering, audits.
• Build deep observability with tracing, latency breakdowns, dashboards.
• Collaborate with research to turn ideas into full-featured products.

Skills

Backend engineering

Distributed systems

Go

Rust

LLM APIs

AWS

GCP

Kubernetes

Postgres

Redis

Tools

Terraform

Envoy

Kubernetes

Job description

Arena Intelligence, Inc. is seeking an experienced backend engineer to build the core infrastructure under our online evaluation systems. You will design low-latency APIs for leaderboards and arenas, implement enterprise-grade features, and ensure observability across distributed systems.

You will work with researchers, engineers, and product leadership as an early member of the infra team, navigating zero-to-one challenges and scaling complex workloads in a startup environment.