Kubernetes Platform Engineer - AI Infrastructure

The application window is expected to close on: 06/12/2026. Job posting may be removed earlier if the position is filled or if a sufficient number of applications are received.

Kubernetes Platform Engineer - AI Infrastructure - hybrid (2013578).
*** hybrid role requires some on-site work activity at Research Triangle Park NC, Dallas TX, or Allen TX office. Meet the Team.

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 traditional models and LLMs. You will lead the technical direction of scalable, reliable systems, managing the Kubernetes control plane and extending platform capabilities through custom controllers and operators. You’ll architect ML platforms, implement Infrastructure as Code with Golang, and drive MLOps best practices.

Partnering closely with data scientists and ML engineers, you’ll enable high-performance AI workloads while leveraging AIOps for automation and reliability. This role requires strong hands‑on on‑prem Kubernetes experience and offers opportunities to mentor engineers and influence platform strategy in a hybrid environment.

• Design, build, and operate large-scale on-prem Kubernetes platforms (Open Shift/Anthos), with ownership of control plane, etc., and cluster lifecycle.
• Architect scalable, multi‑tenant platform infrastructure as the foundation for AI/ML and GenAI workloads.
• Enable and optimize AI/ML workloads, including GPU‑based environments for training, inference, and model deployment.
• Partner with data scientists and ML engineers to onboard and scale ML pipelines and workflows.
• Build platform capabilities using Kubernetes controllers, operators, CRDs, and Golang/Python services.
• Implement Infrastructure as Code, automation, and AIOps‑driven self‑healing using platform telemetry and observability.
• Ensure reliability through performance tuning (scheduling, resource utilization) and participate in on‑call support and incident response.

• 5+ years of software engineering experience, including supporting AI/ML or GPU‑based workloads on Kubernetes platforms.
• 3+ years operating Kubernetes in production with control plane ownership, preferably in on‑prem or self‑managed environments.
• Strong experience with etcd management (backup, restore, recovery) and Kubernetes cluster upgrades.
• Proficiency in Go with experience building Kubernetes controllers/operators, CRDs, and webhooks.
• Deep understanding of Kubernetes internals (API server, scheduler, controller loops, reconciliation patterns).
• Proven ability to debug and operate large‑scale distributed systems in production environments, including participation in on‑call rotations.

• Experience with bare‑metal or on‑prem infrastructure at scale.
• Experience enabling or supporting GPU‑based workloads in Kubernetes environments.
• Familiarity with AI/ML platforms, pipelines, or tooling (e.g., model training, inference, or orchestration).
• Experience building internal developer platforms or platform‑as‑a‑service (PaaS) capabilities.
• Exposure to AIOps, including automation, anomaly detection, or self‑healing systems.
• Experience applying statistical or ML techniques to operational data for reliability, performance, or capacity planning.

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 opportunities to grow and build are limitless. We work as a team, collaborating with empathy to make really big things happen on a global scale. Because our solutions are everywhere, our impact is everywhere.

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