Senior Kubernetes / VKS Platform Engineer

Platform EngineerPlatform EngineerFull TimeRemoteSeniorTeam 11-50

Location

United States

Posted

51 days ago

Salary

0

Seniority

Senior

Job Description

Senior Kubernetes / VKS Platform Engineer

ROI Agency

Senior Kubernetes / VKS Platform Engineer Overview We are looking for a Senior Kubernetes Engineer with hands-on VMware vSphere Kubernetes Service (VKS) experience to support cloud-native workload platforms within VCF private cloud environments. You will provision and manage VKS clusters, enforce governance, and support AI/ML workload infrastructure. Responsibilities - Deploy and manage VKS clusters across multiple VCF projects and namespaces - Configure RBAC, network policies (Antrea/CNI), storage, and cluster backup - Support GPU-enabled VKS clusters for AI/ML workloads where applicable - Integrate Kubernetes platform with Aria Automation self-service catalog - Enforce governance policies across distributed cluster fleets Required Skills - 10+ years data center experience - VMware vSphere Kubernetes Service (VKS) or Tanzu Kubernetes hands-on experience - Kubernetes / K8s administration (CKA preferred) - VMware Cloud Foundation (VCF) environment experience - VMware certifications required Bonus - NVIDIA GPU / vGPU cluster experience - VMware Private AI Foundation exposure - Helm, GitOps (ArgoCD/Flux) - Aria Automation integration experience Work Details - 100% remote | Central or Eastern time zone preferred - ~40 hrs/week across 1–2 end clients | Through EOY, extendable - US Citizen required | 10-year background check - Must not be active on another Broadcom credit engagement - No CA or NY residents unless LLC registered in another state Requirements Required Skills - 10+ years data center experience - VMware vSphere Kubernetes Service (VKS) or Tanzu Kubernetes hands-on experience - Kubernetes / K8s administration (CKA preferred) - VMware Cloud Foundation (VCF) environment experience - VMware certifications required

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Policy Specialist, Ads and Monetization - Platform Policy, Trust & Safety

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ContractRemoteTeam 11-50

Role Description We are looking for a Senior Kubernetes Engineer with hands-on VMware vSphere Kubernetes Service (VKS) experience to support cloud-native workload platforms within VCF private cloud environments. You will provision and manage VKS clusters, enforce governance, and support AI/ML workload infrastructure. - Deploy and manage VKS clusters across multiple VCF projects and namespaces - Configure RBAC, network policies (Antrea/CNI), storage, and cluster backup - Support GPU-enabled VKS clusters for AI/ML workloads where applicable - Integrate Kubernetes platform with Aria Automation self-service catalog - Enforce governance policies across distributed cluster fleets Qualifications - 10+ years data center experience - VMware vSphere Kubernetes Service (VKS) or Tanzu Kubernetes hands-on experience - Kubernetes / K8s administration (CKA preferred) - VMware Cloud Foundation (VCF) environment experience - VMware certifications required Requirements - NVIDIA GPU / vGPU cluster experience (Bonus) - VMware Private AI Foundation exposure (Bonus) - Helm, GitOps (ArgoCD/Flux) (Bonus) - Aria Automation integration experience (Bonus) Work Details - 100% remote | Central or Eastern time zone preferred - ~40 hrs/week across 1–2 end clients | Through EOY, extendable - US Citizen required | 10-year background check - Must not be active on another Broadcom credit engagement - No CA or NY residents unless LLC registered in another state

USA Timezones + 4 moreAll locations: USA Timezones | EST (UTC-5) | UTC-5 to UTC-3 | GMT (UTC+0) | EET (UTC+2)
Zocdoc logo

Staff Data Platform Engineer

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Zocdoc is the beginning of a better healthcare experience for millions of patients every month.

Full TimeRemoteTeam 501-1,000Since 2007H1B Sponsor

• Defining and evolving data contract standards across the company, including schema enforcement, versioning, and validation patterns. • Designing interoperable ingestion and publishing frameworks that enable upstream producers (e.g., product engineering teams) to integrate seamlessly with the data platform. • Building and standardizing APIs, libraries, or SDKs that simplify event logging, schema validation, and contract compliance. • Establishing best practices for schema registry usage and distributed schema validation across streaming and batch systems (e.g., Kafka-based systems). • Designing clear patterns for: • When to use the data lake vs. the warehouse • How curated layers are exposed • How downstream consumers access data safely • Leading reverse ETL and activation architecture to support operational use cases. • Defining and enforcing access control, governance, and compliance standards (e.g., PHI/PII handling, DEID boundaries, RBAC). • Partnering with Product Engineering, Security, Compliance, Analytics Engineering, and Infrastructure to align on standards and long-term direction. • Mentoring engineers and influencing engineering culture around data quality, ownership, and contracts. • Driving adoption of AI-assisted development practices (e.g., cloud-based coding environments, internal AI tooling, or agentic workflows) to accelerate platform delivery. • Designing guardrails for AI access to data systems, including scoped permissions, auditing, and compliance-aware controls. • Partnering with product and AI teams to ensure our data contracts, schemas, and curated layers are AI-consumable and safe by default. • Evaluating how internal data platform assets can power AI use cases and intelligent automation across the company.

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