Backend Engineer
Department: Engineering
Location: Chicago
Employment Type: FullTime
About yeet
yeet is built by a tight-knit group of systems, observability, and kernel nerds who refuse to accept “mystery outages” as normal. We’re a small, high-impact team with domain expertise in Linux, eBPF, performance instrumentation, and developer tooling.
We move fast, ship often, and take deep ownership. If you enjoy operating close to the metal, building tools that real engineers lean on during 3 AM incident sprints, and solving hard problems with minimal overhead, you’ll feel right at home here.
About the role
We’re looking for a Backend Engineer to help us scale the systems behind yeet’s real-time observability platform.
Our backend is composed primarily of Python micro services, but this isn’t just another “wrap an API around Postgres” role.
You’ll be working on streaming systems, high-throughput data ingestion, and async task pipelines that need to move fast, replicate elastically, and stay reliable under load.
About you
You have solid experience building backend services in Python, from design to production.
You’re comfortable with streaming data pipelines, pub/sub, and real-time messaging systems.
You understand how to design for throughput, reliability, and fault tolerance in distributed systems.
You can simulate high-load conditions and deliver code that’s testable, measurable, and production-ready.
You enjoy solving problems that don’t fit neatly into a CRUD API and like thinking about performance trade-offs.
You’re pragmatic: you know when to optimize and when to ship.
Nice To Haves
Experience with Kafka, RabbitMQ, Redis, Postgres, or DuckDB in production environments.
Familiarity with async frameworks like
asyncio,celery, for task queues and background jobs.Hands-on work with real-time protocols (WebSockets, gRPC streaming, event-driven architectures).
Prior exposure to observability or monitoring platforms, especially in high-scale environments.
A track record of building or scaling high-throughput ingestion pipelines for data storage and processing.
Experience with terraform and comfort contributing to infrastructure design.
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