Performance Optimization Lead

2 days ago


San Francisco, California, United States Nextdoor Full time
Distributed Systems Engineer

We're seeking a highly skilled Distributed Systems Engineer to join our Core Services team. As a member of this team, you'll work in a large-scale distributed system environment, identifying opportunities to increase performance, scalability, and resilience.

Our team operates critical high-throughput services that power our platform globally. We've made significant investments in our infrastructure, including a distributed cache with zone-aware routing in Golang, using Istio's Locality-Aware Routing to serve over 20M QPS. Recent projects include introducing Strimzi for deploying Kafka and building a Kubernetes-native Postgres connection pooler.

We value a hybrid employment experience, providing flexibility for our employees. We believe that when our employees are happy and fulfilled, they're better equipped to deliver exceptional results.

Key Responsibilities

In this position, you'll work closely with product engineers to understand their pain points and identify ways to improve developer experience and scalability. You'll also collaborate with other teams to ensure our infrastructure meets the needs of our product engineers.

Our goal is for the infrastructure to handle the heavy lifting, so our product engineers can focus on delivering exceptional results. You'll play a key role in shaping our infrastructure and contributing to the success of our product engineers.

Requirements and Compensation

To succeed in this role, you'll need at least 5 years of experience in high-performance distributed systems engineering, preferably working closely with scaling databases and caches to support fast social product growth. You should have expertise in operating or building distributed datastores, a deep understanding of distributed systems fundamentals, and experience with languages like Golang, Rust, C++, Java, or Python. For this role, we expect to pay between $210,000 - $265,000 annually, based on location and level of proficiency.

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