Pinterest is seeking a Staff Software Engineer, Capacity Engineering. The team is responsible for efficiently managing one of the largest-scale cloud-native infrastructures in the world. This role is highly impactful, as efficiency is an ongoing strategic priority for Pinterest. The role has direct visibility across Pinterest Engineering and with Engineering and company leadership. The team is looking for a candidate with a strong background in implementing performance and efficiency projects on large scale distributed systems. In this individual-contributor role you will own and drive performance and efficiency for a core area of Capacity Engineering, partnering with the company-wide efficiency lead and collaborating with performance and efficiency leaders across the organization.

What you’ll do:

• Drive efficiency in large-scale shared environments like Kubernetes, including scheduling optimization, resource-overhead reduction, and resource isolation in multi-tenant clusters
• Improve the performance and efficiency of large scale distributed systems that drive Pinterest systems
• Use profiling and performance tooling fluently to root-cause performance and efficiency problems, propose solutions, and partner with the owning teams to implement and validate them
• Collaborate with Infrastructure Engineering and SRE teams in their mission to deliver highly available, resilient, secure and efficient foundations for Pinterest’s tech stack
• Leverage AI to scale the impact of yourself and the team, including:
  • Accelerate performance investigations (e.g. quickly distill logs/metrics/traces and prior learnings) while verifying findings through measurement and testing
  • Build tooling and agents that allow users to self-serve efficiency insights and recommendations
  • Iterate faster on optimization approaches and rollout plans, then validate impact with experiments and production guardrails
    
    

What we’re looking for:

• Bachelor’s degree in computer science, a related field or equivalent experience
• Deep understanding of infrastructure capacity and performance, with a strong command of system and hardware fundamentals (how things work under the hood: CPU, memory, OS scheduling, I/O)
• Experience leading efficiency initiatives at scale on Kubernetes or other large scale shared infrastructure
• Strong technical and performance engineering skills, including fluency with profiling and performance tools such as perf and async-profiler, to root-cause complex, ambiguous problems and collaborate with stakeholders to drive solutions to implementation
• Experience building and managing highly available distributed applications at scale
• Proficiency in software development languages such as Java, Python and C++
• Excellent skills in communicating complex technical issues
• Experience with AWS or similar cloud environments
• Demonstrated ability to use AI to improve speed and quality in your day-to-day workflow for relevant outputs
• Strong track record of critical evaluation and verification of AI-assisted work (e.g., testing, source-checking, data validation, peer review)
• High integrity and ownership: you protect sensitive data, avoid over-reliance on AI, and remain accountable for final decisions and deliverables
• Bonus points for the following:
  • Hands-on experience with large, cloud-native multi-tenant platforms at Internet scale

In-Office Requirement Statement: 

• We let the type of work you do guide the collaboration style. That means we're not always working in an office, but we continue to gather for key moments of collaboration and connection. 
• This role will need to be in the office for in-person collaboration 1-2 times/month and therefore can be situated anywhere in the country. 

Relocation Statement:

• This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.

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