Staff Platform Engineer

Join our team as a Staff Platform Engineer, where you'll set the technical direction for our platform, lead high-complexity initiatives, and shape a platform that integrates AI agents as first-class users. You'll work across teams, build self-service automation, and establish scalable infrastructure to enhance developer experience and productivity.

• Set technical direction for the platform across teams, lead high-complexity initiatives, and shape a platform where AI agents are first-class users.
• Build self-service automation, shared standards, and scalable AWS and GCP infrastructure that let product teams ship faster and safer.
• Drive clarity through ambiguity, take on loosely-defined problems, validate critical assumptions, and create alignment with stakeholders.
• A track record of leading high-complexity, cross-team infrastructure initiatives that delivered measurable improvements in reliability, developer productivity, performance, or cost
• Solid command of AWS core services (EC2, EKS, IAM, VPC, ALB, S3) — GCP and/or Azure experience a plus — and networking/security fundamentals
• Strong programming ability in at least one language (Golang or Python preferred) and fluency with IaC tooling (Terraform)
• 8+ years of experience in software engineering, DevOps, or Site Reliability Engineering, with deep hands-on time in cloud infrastructure
• Curiosity and conviction about AI as a force multiplier in infrastructure work — whether that's using AI-assisted development tools to ship faster or building platforms and tooling that help your teammates get more leverage from AI in their day-to-day work
• Bachelors Degree in Computer Engineering or related field
• Strong communicator — you can break down complex topics for varied audiences, drive cross-team decisions to a timely close, and default to collaborative problem solving
• A history of setting technical standards and patterns that other teams adopted — influencing outcomes well beyond your own keyboard, often without direct authority
• Deep production experience operating Kubernetes (EKS, GKE, AKS, or on-prem) and containerized applications at meaningful scale
• A pragmatic, business-aligned engineering mindset, a bias for action, and a habit of continuous learning and knowledge sharing
• Comfort navigating ambiguity by validating assumptions early and using data to de-risk technical decisions — with the judgment to say no, reshape scope, and protect the team's focus when the expected impact no longer justifies the work
• Deep familiarity with GitOps workflows and the CNCF ecosystem (Argo, Helm, Backstage, Envoy, and friends), and a point of view on where they're heading