Staff Software Engineer — Large-Scale Capacity & Performance

Pinterest; California (MO); Hybrid; USD 177,000 - 365,000; Full time

Benefits offered by this job

Equity eligible

Flexible work model

Job summary

Pinterest is seeking a Staff Software Engineer for Capacity Engineering to own performance and efficiency across large-scale, cloud-native systems. You will lead initiatives in Kubernetes environments, profile complex workloads, and partner with SRE and Infra teams to deliver reliable foundations. AI-driven tooling and self-serve insights accelerate improvements.

The role emphasizes ownership, deep hardware and OS understanding, and delivering measurable impact at scale. US-based applicants only.

Qualifications

• Bachelor’s degree in computer science or related field, or equivalent experience.
• Strong understanding of infrastructure capacity, performance, and OS concepts.
• Experience leading efficiency initiatives at scale on Kubernetes or similar infra.
• Proficiency with Java, Python and C++, and profiling tools to diagnose issues.
• Experience building highly available distributed applications and communicating complex technical topics.

Responsibilities

• Drive efficiency in large-scale Kubernetes environments, including scheduling and isolation.
• Improve performance and efficiency of large-scale distributed systems supporting Pinterest.
• Use profiling tools to root-cause performance issues and implement solutions with owning teams.
• Collaborate with Infrastructure Engineering and SRE to deliver reliable foundations.
• Leverage AI to scale impact, build self-serve insights, and validate with experiments.

Skills

Java

Python

C++

Performance profiling

Distributed systems

System design

Communication

AI usage

Education

Bachelor's degree in Computer Science

Tools

Kubernetes

Perf

async-profiler

AWS

Job description

Pinterest is seeking a Staff Software Engineer for Capacity Engineering to own performance and efficiency across large-scale, cloud-native systems. You will lead initiatives in Kubernetes environments, profile complex workloads, and partner with SRE and Infra teams to deliver reliable foundations. AI-driven tooling and self-serve insights accelerate improvements.

The role emphasizes ownership, deep hardware and OS understanding, and delivering measurable impact at scale. US-based applicants only.