Site Reliability Engineer

Location

San Francisco

Employment Type

Full time

Location Type

On-site

Department

Engineering

Compensation

$150K – $200K

Why do companies use LiteLLM Enterprise

Companies use LiteLLM Enterprise once they put LiteLLM into production and need enterprise features like Prometheus metrics (production monitoring) and need to give LLM access to a large number of people with SSO (secure sign on) or JWT (JSON Web Tokens).

What you will be working on

Skills: Python, FastAPI, PostgreSQL, Redis, Kubernetes, Prometheus, performance profiling As the SRE, you'll own the reliability and performance of the LiteLLM proxy in production. Our users run LiteLLM as a critical gateway handling millions of LLM requests — when it goes down, their entire AI stack goes down. You'll work directly with the CEO and CTO on critical projects including:

Fixing OOM issues — e.g. Prisma Query Engine unable to recover from OOMKill in K8s deployments, unbounded in-memory buffers in spend log transactions
Solving database connection problems — e.g. database query limits getting reached under load, spend logs loading extremely slowly, Prisma connection pool exhaustion
Fixing race conditions and deadlocks — e.g. max_parallel_requests deadlocking API keys after provider timeouts (counter never released, Redis reset required), PodLockManager releasing another pod's lock, in-memory cache increment race conditions
Performance optimization — e.g. update_database() doing 7 deep copies per request in the spend tracking hot path, health check fan-out overloading startup
Improving Redis/cache reliability — e.g. budget limiter reading stale Redis data, cache sync issues between in-memory and Redis layers
Production monitoring — making Prometheus metrics accurate (fixing missing/inf budget metrics), adding alerting, improving observability for multi-pod deployments
Making the proxy self-healing — graceful degradation when DB/Redis is temporarily unavailable, connection retry logic, proper health checks

What is our tech stack

The tech stack includes Python, FastAPI, Redis, Postgres, Prisma ORM, Kubernetes, Prometheus, Docker.

Who we are looking for

1-4 years of experience running Python services in production at scale
Experience debugging OOMs, memory leaks, connection pool issues, and race conditions
Comfortable with PostgreSQL (query optimization, connection pooling, PgBouncer) and Redis
Kubernetes experience — you've dealt with pod restarts, resource limits, health probes, and multi-replica coordination
Familiarity with Prometheus/Grafana for monitoring and alerting
Passion for open source and user engagement
Strong work ethic and ability to thrive in small teams
Eagerness to talk to users and help solve real problems — our GitHub issues are full of production debugging sessions and you'd be jumping into those directly

About LiteLLM

LiteLLM (https://github.com/BerriAI/litellm) is a Python SDK, Proxy Server (LLM Gateway) to call 100+ LLM APIs in OpenAI format - [Bedrock, Azure, OpenAI, VertexAI, Cohere] and is used by companies like Rocket Money, Adobe, Twilio, and Siemens.