Senior Kubernetes Architect & Cloud-Native SME

MACHINE LEARNING TECHNOLOGIES LLC; North Charleston (SC); On-site; USD 94,000 - 134,000; Full time

Job summary

MACHINE LEARNING TECHNOLOGIES LLC seeks a high-level Kubernetes SME to design, implement, and manage enterprise Kubernetes environments. This role drives multi-cloud cluster operations, automation, and performance optimization in collaboration with application teams.

The ideal candidate has deep hands-on Kubernetes experience, proficiency with GitOps tooling, and strong documentation and mentorship capabilities. U.S. work authorization required, with potential for extended engagement.

Qualifications

• Must be eligible to obtain and/or maintain a DoD Secret security clearance.
• Deep hands-on Kubernetes experience with multi-cloud orchestration and operations.
• Experience designing, provisioning, administer, and troubleshooting production Kubernetes environments.
• Familiarity with AKS, EKS, or GKE and container tooling like Docker/Buildah/Podman.

Responsibilities

• Design, implement, manage, and optimize enterprise-grade Kubernetes environments.
• Onboard workloads with application teams and establish deployment patterns.
• Architect multi-cloud cluster deployments and automate with IaC.
• Develop reusable automation templates and standards across environments.
• Provide leadership, knowledge transfer, and mentorship to junior engineers.

Skills

Kubernetes expertise

Cloud-native infra

GitOps workflows

Documentation & mentoring

Security/compliance knowledge

Education

BS Degree in a technical field

Security/Scrum certifications eligibility

5+ years Kubernetes experience

Tools

Argo CD

Flux

AKS / EKS / GKE

Docker/Buildah/Podman

Istio/Linkerd

NGINX/HAProxy/Traefik

Helm, Kustomize, Operators

OPA/Gatekeeper, Kyverno, Falco

Terraform / Ansible

Git, Jenkins, YAML, CI/CD

Job description

MACHINE LEARNING TECHNOLOGIES LLC seeks a high-level Kubernetes SME to design, implement, and manage enterprise Kubernetes environments. This role drives multi-cloud cluster operations, automation, and performance optimization in collaboration with application teams.

The ideal candidate has deep hands-on Kubernetes experience, proficiency with GitOps tooling, and strong documentation and mentorship capabilities. U.S. work authorization required, with potential for extended engagement.