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Senior Kubernetes Platform Engineer - AI/ML Infrastructure - hybrid (2013054)

***hybrid role requires some work activity on-site at Research Triangle Park NC, Dallas TX or Allen TX office

Join our Platform Engineering team to design, build, and operate large-scale, on-prem Kubernetes infrastructure powering next-generation AI/ML platforms, including GPU-enabled environments for both traditional ML and state-of-the-art LLM workloads.

You will be pivotal in defining and evolving a highly scalable Kubernetes platform that serves as the foundation for AI/ML workloads. This role combines deep Kubernetes platform engineering with AI/ML infrastructure enablement, ensuring performance, reliability, and scalability across distributed systems.

You will lead technical direction across Kubernetes control plane operations, cluster lifecycle management, and platform extensibility, while working closely with data scientists, ML engineers, and infrastructure teams to support production AI workloads at scale.

This is a senior individual contributor role focused on platform ownership, engineering excellence, and driving reliability and automation across complex distributed environments.

Your Impact / Core Responsibilities

• Architect, build, and operate large-scale on-prem Kubernetes platforms (OpenShift/Anthos), including control plane and etcd lifecycle management

• Define and evolve scalable, multi-tenant platform architecture supporting AI/ML and GPU-based workloads

• Enable and optimize ML workloads including training, inference, and LLM deployment pipelines on Kubernetes

• Build platform extensions using Kubernetes controllers, operators, CRDs, and Golang-based services

• Implement Infrastructure as Code and automation to improve scalability, consistency, and operational efficiency

• Drive AIOps capabilities using telemetry, automation, anomaly detection, and self-healing systems for platform reliability

• Improve observability (metrics, logs, traces) and optimize resource utilization, scheduling, and cluster performance

• Partner with ML engineers and data scientists to operationalize ML workflows and ensure platform readiness for AI workloads

• Participate in on-call rotations, owning incident response, reliability, and continuous operational improvement

• Mentor engineers and contribute to defining platform engineering standards and best practices

Minimum Qualifications

• 8+ years of software engineering experience

• 4+ years of hands-on Kubernetes production experience with control plane ownership

• Strong experience operating on-prem or self-managed Kubernetes environments

• Deep expertise in etcd management (backup, restore, recovery, upgrades)

• Strong proficiency in Go with experience building Kubernetes controllers, operators, CRDs, and webhooks

• Deep understanding of Kubernetes internals (API server, scheduler, controller loops, reconciliation)

• Experience supporting AI/ML or GPU-based workloads on Kubernetes platforms

• Proven experience operating and debugging large-scale distributed systems

• Experience participating in on-call rotations and production incident management

Preferred Qualifications

• Experience with bare-metal or enterprise on-prem infrastructure at scale

• Exposure to AI/ML platforms and tooling (e.g., Kubeflow, MLflow, distributed training systems)

• Experience building internal developer platforms or platform-as-a-service (PaaS) systems

• Familiarity with AIOps concepts such as automated remediation and predictive operations

• Experience applying data-driven or ML-based techniques for system reliability or capacity planning

• Contributions to Kubernetes, CNCF, or other open-source ecosystems

Why Cisco? 

At Cisco, we’re revolutionizing how data and infrastructure connect and protect organizations in the AI era – and beyond. We’ve been innovating fearlessly for 40 years to create solutions that power how humans and technology work together across the physical and digital worlds. These solutions provide customers with unparalleled security, visibility, and insights across the entire digital footprint.

Fueled by the depth and breadth of our technology, we experiment and create meaningful solutions. Add to that our worldwide network of doers and experts, and you’ll see that the o