Kubernetes Platform Engineer

Seeking a Kubernetes Platform Engineer to support the production rollout of an existing enterprise Kubernetes environment and assist with AI gateway evaluations and deployments.

This resource will serve as a hands-on engineering contributor embedded within the customer environment, leveraging established platform designs and deployment manifests to complete production implementation efforts, troubleshoot issues, and support AI platform initiatives.

This is a highly technical, execution-focused role requiring strong Kubernetes, Linux, networking, storage, automation, and platform troubleshooting experience.

Primary Responsibilities

• Execute and validate production Kubernetes deployments using existing platform designs and deployment manifests
• Troubleshoot Linux, container, networking, storage, and cluster-related issues
• Deploy and support AI gateway proof-of-concepts and inference platform integrations
• Integrate and validate model-serving endpoints
• Evaluate authentication, routing, rate limiting, observability, and platform performance
• Support Kubernetes networking, ingress, load balancing, DNS, storage, and security configurations
• Maintain deployment automation workflows and operational runbooks
• Document findings and provide knowledge transfer to customer teams
• Collaborate with platform engineering teams to resolve infrastructure and application issues
• Provide recommendations related to platform performance, scalability, and operational readiness

• Proven experience deploying and supporting production Kubernetes environments
• Strong experience with on-premises or bare-metal Kubernetes deployments
• Advanced Linux administration experience
• Experience with container runtimes and containerized application deployments
• Strong knowledge of:
• Kubernetes Networking
• DNS
• Ingress Controllers
• Load Balancing
• Persistent Storage
• RBAC
• Secrets Management
• TLS/Certificates
• Experience with Helm, Kustomize, YAML, and Git-based deployment workflows
• Python and/or Bash automation experience
• Experience with Prometheus, Grafana, or similar monitoring platforms
• Experience integrating APIs, AI services, or inference endpoints
• Ability to work independently within a customer environment

Preferred Qualifications

• NVIDIA GPU infrastructure experience
• GPU Operator implementation and support
• GPU monitoring and optimization
• vLLM or similar LLM-serving platforms
• AI/API Gateway products (Solo.io, Kong, Apigee, NGINX Gateway, etc.)
• RDMA, InfiniBand, or RoCEv2 experience
• NCCL performance testing
• Slurm workload scheduler experience
• Certified Kubernetes Administrator (CKA)