Kubernetes Platform Engineer – AI Infrastructure
Cisco · San Jose, California, United States
Hybrid Full-time Posted 4 days ago
About this role
The application window is expected to close on: 06/26/2026<p><span style="color:#000000"><b><span style="font-size:14px">Job posting may be removed earlier if the position is filled or if a sufficient number of applications are received</span></b><span style="font-size:14px">.</span></span></p><p></p><p>Kubernetes Platform Engineer – AI Infrastructure - hybrid (2013055)</p><p><br />***hybrid role - requires some work activity to be on-site in San Jose CA office</p><p></p><p><b>Meet the Team</b></p><p>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.</p><p></p><p><b>Your Impact / Responsibilities </b>as a <b>Kubernetes Platform Engineer</b>, you will:</p><ul><li><p>Design, build, and operate large-scale on-prem Kubernetes platforms (OpenShift/Anthos), with ownership of control plane, etcd, and cluster lifecycle.</p></li><li><p>Architect scalable, multi-tenant platform infrastructure as the foundation for AI/ML and GenAI workloads.</p></li><li><p>Enable and optimize AI/ML workloads, including GPU-based environments for training, inference, and model deployment.</p></li><li><p>Partner with data scientists and ML engineers to onboard and scale ML pipelines and workflows.</p></li><li><p>Build pla
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