Staff Software Engineer, Cloud Platform - Pinterest

Pinterest operates at a massive scale, serving 500+ million users globally with billions of requests daily. Our Cloud Platform team owns the foundational infrastructure technology that powers Pinterest's entire ecosystem. We're building PinCompute, our next-generation Kubernetes-based platform that will eventually run all of Pinterest's workloads and services. This platform represents a multi-year transformation of how we build, deploy, and operate services at Pinterest scale.

We're looking for an exceptional Staff Software Engineer to lead the technical strategy and execution of our cloud infrastructure initiatives. You'll shape how Pinterest engineers build and deploy services, driving innovation in areas like container orchestration, service mesh, developer experience, and cloud-native architectures at Internet scale.

What you'll do

• Define and drive the multi-year technical strategy for Pinterest's Cloud Infrastructure platform, focusing on our Kubernetes-based PinCompute platform that hosts thousands of services and petabytes of data.
• Lead the design and implementation of complex, cross-team infrastructure initiatives including service mesh adoption, multi-region architectures, and developer platform capabilities
• Partner with teams across Pinterest to modernize our infrastructure stack, improving developer velocity while reducing operational complexity and costs
• Architect solutions for critical infrastructure challenges including auto-scaling, resource optimization, traffic management, and service reliability at Pinterest scale
• Drive adoption of cloud-native patterns and technologies across the engineering organization, establishing best practices and reference architectures
• Provide technical leadership during critical incidents and architect solutions to prevent recurrence
• Influence the broader Kubernetes and cloud-native community through open source contributions and conference presentations
• Mentor senior engineers and technical leads across multiple teams, developing the next generation of infrastructure leaders
• Thoughtfully leverage AI tools to speed up design, coding, debugging, and documentation, while applying your own critical thinking to validate outputs and explain how you used AI in your workflow.
• Shape our AI-assisted engineering practices by sharing patterns, guardrails, and learnings with the team so we can safely increase our impact without compromising code quality, reliability, or candidate expectations.

What we're looking for

• 7+ years of experience building and operating large-scale production infrastructure.
• Expertise with multi-tenant cluster orchestration systems such as Kubernetes, container orchestration, and cloud-native architectures is beneficial.
• Proven track record of leading multi-year infrastructure transformations at internet-scale companies (billions of requests/day, thousands of services).
• Background in service mesh technologies and traffic management at scale.
• Expertise in infrastructure-as-code, GitOps, and modern CI/CD practices.
• Experience building developer platforms and tools that improve engineering productivity across hundreds of engineers.
• Proficiency in C++, Go, or Java, with ability to contribute to infrastructure codebases.
• Track record of driving cross-organizational technical initiatives with measurable business impact
• Experience using AI coding assistants and agentic tools as a force-multiplier, and equally comfortable solving problems from first principles when those tools aren’t available.
• Bachelor's/Master's degree in Computer Science or equivalent experience.

Relocation Statement:

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

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 per week and therefore needs to be in a commutable distance from one of the following offices: Zurich.

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