About the company
ServiceNow is the AI control tower for business reinvention. Our ServiceNow AI platform brings together any AI, any data, and any workflow— helping 85% of the Fortune 500® work smarter, faster, and better.
Responsibilities
- Set the technical direction for our cloud-native platform across multiple engineering teams and organizations, defining the architecture and standards for how Kubernetes, distributed systems, and hyperscaler infrastructure are built and operated at scale.
- Own the hardest, most ambiguous technical problems in the platform domain — multi-cloud topology, control-plane design, workload isolation, identity and trust fabric, and reliability at the scale of hundreds of clusters and dozens of product workloads.
- Partner with engineering fellows, principal engineers, and other senior technical leaders to drive consistent architectural decisions and the adoption of best practices across the entire platform ecosystem.
- Identify and mitigate the biggest technical risks in initiatives with C-suite visibility, and be the person leadership trusts to make the call on managed vs. self-managed tradeoffs, substrate portability, and multi-hyperscaler strategy.
- Where you see the need, personally design and build the critical components — control planes, operators, infrastructure abstractions, and the systems other teams build on top of.
- Mentor staff and principal engineers and shape the next generation of the organization’s technical leadership.
Requirements
- Experience leveraging or critically thinking about how to integrate AI into engineering and platform work — whether using AI-powered tooling, automating operational workflows, building agentic systems for fleet visibility and operations, or reasoning about AI’s impact on how infrastructure is built and run.
- 12+ years of experience designing, building, and operating large-scale distributed systems in production, with deep expertise running Kubernetes at scale (multi-cluster, multi-region, multi-tenant).
- Hands-on, authoritative experience across one or more major hyperscalers (AWS, Azure, GCP), including their managed Kubernetes offerings (EKS, AKS, GKE) and the networking, IAM, and capacity tradeoffs that come with each.
- A proven track record of providing technical leadership across multiple engineering teams, influencing architecture and direction without relying on positional authority.
- Deep expertise in the core building blocks of a modern platform: the operator/controller pattern, infrastructure-as-code and control planes (e.g., Crossplane), GitOps-based delivery, container networking (CNI), and service mesh.
- Strong programming skills in Go and fluency across the clo