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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.
- 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 AI, and remain accountable for final decisions and deliverables.
- Preferred qualifications
- Experience managing a Production Engineering, Site Reliability Engineering, or similarly production-focused infrastructure team.
- Experience with managed Kubernetes services, especially Amazon EKS or Google Kubernetes Engine (GKE).
- Experience operating a large Kubernetes fleet or multi-tenant compute platform.
- Experience with infrastructure as code, Kubernetes lifecycle management, observability, networking, or production upgrades.
- Experience with GPU or machine-learning infrastructure, capacity management, cloud cost, or resource allocation.
- Preferred qualifications
In-Office Requirement Statement:
- We recognize that the ideal environment for work is situational and may differ across departments. What this looks like day-to-day can vary based on the needs of each organization or role.
- This role will need to be in the office for in-person collaboration 1-2 times per quarter 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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At Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide greater transparency, we are sharing the base salary range for this position. The position is also eligible for equity. Final salary is based on a number of factors including location, travel, relevant prior experience, or particular skills and expertise.
Information regarding the culture at Pinterest and benefits available for this position can be found here.
Our Commitment to Inclusion:
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