Site Reliability Engineer

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