Senior Manager, Kubernetes Runtime Engineering

NVIDIA•Seattle, CA

21h

About The Position

The NVIDIA Kubernetes Engine (NKE) team is looking for a technical leader to lead the Runtime Engineering team responsible for the full configuration lifecycle of NKE tenant workload clusters. This team is responsible for software components that keep GPU workloads reliable and secure at scale. Their scope includes cluster bootstrapping, node configuration, and the container execution environment, including NVIDIA's AI Container Runtime (AICR). You will work across networking, storage, GPU resource management, and cluster security to deliver a production-grade, multi-tenant Kubernetes platform. Your team's decisions directly shape the runtime foundation that internal and external customers depend on.

Requirements

BS/MS degree in Computer Science or related field (or equivalent experience)
12+ overall years of relevant experience designing and delivering large-scale distributed software systems, including 5+ years of people-management experience leading, developing, and scaling high-performing software engineering teams responsible for complex, production-critical software.
Experience leading a group of engineers with varying specializations and seniority levels — bridging runtime, networking, and security fields is a core part of this role
Kubernetes internals knowledge — not just usage; you understand how the scheduler, kubelet, API server, and admission controllers interact
Cluster lifecycle management experience — Cluster API, kubeadm, or equivalent; experience leading fleet-scale cluster provisioning and upgrades
Security and compliance posture — CIS Kubernetes Benchmark, pod security admission, image signing, supply chain integrity
Proven ability to design and implement maintainable APIs for consumers
Familiarity with Identity and Access Management approaches
Excel in managing up, down, and across organizations
Demonstrated ability to reach cross-organization consensus without all the details

Nice To Haves

Prior experience with NVIDIA GPU Operator, DCGM Exporter, or NVLink-aware scheduling
Experience running Kubernetes at hyperscale with GPU node pools
Track record of upstream open source contributions in the Kubernetes or any open source runtime ecosystem
Experienced, persuasive, and effective interpersonal skills — written, verbal, and in front of engineering leadership
Demonstrated skills in coaching, analysis, problem solving, and short/long-term technical planning

Responsibilities

Be responsible for the build, implementation, and operational reliability of cluster configurations for NKE tenant workloads across all supported topologies
Manage a team of engineers coordinating the entire container runtime stack: AICR, GPU management operator, DCGM, and related node-level components
Drive architecture decisions for cluster networking (CNI), storage (CSI), cluster HA , and GPU resource partitioning (MIG, MPS, time-slicing)
Define and implement cluster hardening standards, RBAC models, pod security policies, and multi-tenancy isolation boundaries
Partner with NKE platform, infrastructure, and cybersecurity teams to integrate new capabilities and resolve cross-cutting runtime concerns
Build and maintain tooling for AICR lifecycle management — provisioning, upgrades, configuration drift detection, and remediation
Represent the runtime team in architecture reviews, roadmap planning, and customer communications with NVIDIA leadership
Contribute to open source communities anywhere NKE has upstream dependencies or influence