Manager II, Engineering - Kubernetes Platform

Job description

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the  flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . Pinterest is seeking a Manager II, Engineering to lead our Kubernetes Platform team. The team builds and operates the infrastructure and tooling that help engineers run reliable, scalable services on Kubernetes. You will lead engineers working on production systems that need to be dependable, secure, efficient, and straightforward for customers to use. You will work with partner teams across Pinterest to improve the platform, reduce operational friction, and make sound decisions when reliability, speed, cost, and security pull in different directions. What you’ll do: • Lead a team of engineers responsible for Kubernetes platform infrastructure and the systems that support it. • Establish the team’s 12-month strategy, roadmap, and success measures. • Improve the reliability, security, scalability, and operational efficiency of the platform. • Drive architecture and technical decisions, including in areas that are new to you. Build context quickly, involve the right experts, and make decisions when the team needs direction. • Build automation, standard configurations, and self-service paths that reduce manual work for both the team and its customers. • Set a high bar for how the team operates production systems, including service health, observability, on-call, incident response, and safe changes. • Partner with engineering, product, finance, security, and cloud-provider teams on shared technical and operational challenges. • Recruit, coach, and develop engineers; empower senior technical leaders; and sustain an inclusive, accountable team. • Use AI to accelerate analysis, investigations, documentation, and repeatable workflows while applying judgment and verification to ensure quality. What we’re looking for: • Bachelor’s degree in Computer Science, a related field, or equivalent practical experience. • Minimum 3 years of experience managing engineering teams in infrastructure, platform engineering, Site Reliability Engineering, cloud systems, distributed systems, or similar technical areas. • Experience managing and developing teams that build or operate large-scale cloud infrastructure, Kubernetes platforms, shared compute platforms, or other production systems. • Experience setting a multi-quarter technical strategy and delivering through senior engineers. • Technical experience in public cloud, highly available distributed systems, Kubernetes or shared-compute platforms, and production operations. • A strong reliability mindset and experience leading teams responsible for the operational quality of production systems. • Experience leading cross-functional infrastructure programs and communicating reliability, security, cost, capacity, and delivery tradeoffs to partner teams. • Demonstrated ability to use AI to improve speed and quality in day-to-day work. • Strong record of evaluating AI-assisted work through testing, source checking, data validation, or peer review. • High integrity and ownership: you protect sensitive data, avoid over-reliance on A