Principal Data Platform Software Engineer - Distributed Systems - Kubernetes

ServiceNow•Santa Clara, CA

3d•Remote

About The Position

As a Principal Engineer, you will help to set the technical direction for our cloud-native platform across multiple engineering teams and organizations. You will be part of a team defining the architecture and standards for how Kubernetes, distributed systems, and hyperscaler infrastructure are built and operated at scale. You will assist in solving 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. You will work with a team of principal engineers and engineering fellows, and other senior technical leaders to help drive consistent architectural decisions and the adoption of best practices across the entire platform ecosystem. You will assist in identifying and mitigating the biggest technical risks in initiatives with C-suite visibility. You will help mentor staff and senior 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.
15+ years of experience with a Bachelor degree or 12+ years with a Masters degree, designing, building, and operating large-scale distributed systems in production.
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 associated tradeoffs.
Proven track record of providing technical leadership across multiple engineering teams, influencing architecture and direction without relying on positional authority.
Deep expertise in 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 cloud-native platforms across multiple engineering teams.
Define architecture and standards for Kubernetes, distributed systems, and hyperscaler infrastructure at scale.
Solve complex technical problems in multi-cloud topology, control-plane design, workload isolation, identity and trust fabric, and reliability.
Drive consistent architectural decisions and adoption of best practices across the platform ecosystem.
Identify and mitigate technical risks in initiatives with C-suite visibility.
Mentor staff and senior engineers and shape technical leadership.