Distinguished Engineer / Architect - Cloud Platform — Kubernetes, Hyperscalers

ServiceNow•Santa Clara, CA

2d•$254,500 - $445,400•Hybrid

About The Position

This role serves as an org-wide technical authority, setting direction across multiple engineering organizations and owning the most challenging and ambiguous problems within the cloud platform domain. The individual will define the architecture and standards for building and operating Kubernetes, distributed systems, and hyperscaler infrastructure at scale. Key responsibilities include addressing complex technical challenges like multi-cloud topology, control-plane design, workload isolation, identity and trust fabric, and ensuring reliability across hundreds of clusters and dozens of product workloads. The role involves partnering with other senior technical leaders to drive consistent architectural decisions and best practices, identifying and mitigating technical risks, and making critical decisions on managed vs. self-managed tradeoffs, substrate portability, and multi-hyperscaler strategy. The engineer will also be responsible for designing and building critical components, and mentoring staff and principal engineers to shape future 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 cloud-native ecosystem.

Nice To Haves

Experience designing identity and trust fabrics for distributed systems — workload identity, mTLS, and standards such as SPIFFE/SPIRE.
Experience with multi-tenant workload isolation and runtime security (e.g., Kata Containers, sandboxed runtimes).
Experience building and operating platforms for regulated or federal markets (FedRAMP, air-gapped or self-hosted distribution, OCI bundling).
Experience with observability at scale — metrics, tracing, and SLO-driven operations across a large fleet.
A platform-as-product mindset: treating internal engineering teams as customers and the platform as a product with a roadmap, contracts, and a delivery pipeline.

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 deepest 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.
Design and build critical components — control planes, operators, infrastructure abstractions, and the systems other teams build on top of — where the need is identified.
Mentor staff and principal engineers and shape the next generation of the organization’s technical leadership.