Senior Kubernetes Platform Engineer - AI/ML Infrastructure
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 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.
Requirements
- 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
Nice To Haves
- 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
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
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 (for non-sales roles)
- performance-based incentive pay (for sales roles)
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
