Kubernetes Platform Engineer - AI Infrastructure

Cisco•Research Triangle Park, NC

1d•$126,500 - $252,000•Hybrid

About The Position

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.

Requirements

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

Nice To Haves

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

Responsibilities

Design, build, and operate large-scale on-prem Kubernetes platforms (OpenShift/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.

Benefits

medical, dental and vision insurance
a 401(k) plan with a Cisco matching contribution
paid parental leave
short and long-term disability coverage
basic life insurance
grants of Cisco restricted stock units
10 paid holidays per full calendar year
1 floating holiday for non-exempt employees
1 paid day off for employee’s birthday
paid year-end holiday shutdown
4 paid days off for personal wellness
16 days of paid vacation time per full calendar year (non-exempt)
flexible vacation time off program (exempt)
80 hours of sick time off provided on hire date and each January 1st thereafter
up to 80 hours of unused sick time carried forward
Additional paid time away may be requested to deal with critical or emergency issues for family members
Optional 10 paid days per full calendar year to volunteer
annual bonuses (non-sales roles)
performance-based incentive pay (sales roles)