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# Infrastructure Engineer

- **Company:** PEOPLE INC.
- **Location:** San Francisco, CA, United States
- **Experience:** Experienced
- **Salary:** $200,000.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Audit Trail, Cloud Computing, Databases, Programming Tools, Distributed Systems, PostgreSQL, Role-Based Access Control, Redis, OpenAI, Single Sign-On, Data Streaming, Google Cloud, Large Language Models, Backend, Rate Limiting, Usage Tracking, Kubernetes, LiteLLM, Machine Learning Operations, Api Gateway, Terraform, Dynatrace
- **Published:** November 7, 2026
- **Apply:** https://www.juju.com/job/28_25196_ce3a965a1d5196acd7236531fc4b08e9

## About the Role

* 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., * 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.).

## Description

* 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.