Virtualization & Orchestration Engineer

Opedia Technologies

Virtualization & Orchestration Engineer building AI infrastructure platforms. Focused on GPU compute for AI workloads in a hybrid environment.

Posted 7/21/2026full-timeBellevue • Washington • 🇺🇸 United StatesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and operating Kubernetes-based orchestration systems for GPU-intensive AI and HPC workloads, with a strong focus on infrastructure automation and resource management. Proven ability to enhance the reliability and scalability of orchestration platforms while collaborating with cross-functional teams.

Highest-signal resume keywords

Kubernetes OrchestrationGPU Cluster ProvisioningInfrastructure AutomationLinux-Based InfrastructureDistributed Systems

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Applicant Tracking System Keywords

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Hard Skills

KubernetesVirtualization TechnologiesGPU Scheduling TechnologiesInfrastructure as CodeResource ManagementWorkload SchedulingCluster Lifecycle OperationsAI Infrastructure SupportMulti-Tenant InfrastructureHigh-Performance Networking

Soft Skills

Problem-SolvingCollaborationAdaptability

Tools & Technologies

SlurmNVIDIA GPU OperatorContainer OrchestrationCloud ProvidersHPC Environments

Industry Keywords

AI WorkloadsHPC WorkloadsDistributed ComputingInfrastructure PlatformsOperational Maturity

Tech Stack

Tools & technologies

CloudDistributed SystemsKubernetesLinux

About the role

Key responsibilities & impact

Design and build virtualization infrastructure supporting GPU-intensive AI and HPC workloads.
Develop and operate Kubernetes-based orchestration systems for GPU cluster provisioning and workload scheduling.
Build automated provisioning systems that enable GPU capacity to be allocated, scaled, and reclaimed efficiently across multiple tenants.
Design solutions for workload placement, resource management, and cluster lifecycle operations.
Partner closely with hardware, networking, infrastructure, and AI platform teams to ensure orchestration systems align with real-world cluster architectures and constraints.
Improve the reliability, security, scalability, and operational maturity of the orchestration platform.
Build tooling and automation that simplifies infrastructure management and improves developer and customer experiences.
Contribute to architectural decisions, engineering standards, and best practices as the platform evolves.

Requirements

What you’ll need

Strong hands-on experience with Kubernetes and container orchestration in production environments.
Experience designing, building, and operating large-scale infrastructure platforms.
Background with virtualization technologies supporting cloud, HPC, GPU, or distributed computing environments.
Understanding of GPU cluster provisioning, workload scheduling, and resource management.
Experience with Linux-based infrastructure and distributed systems concepts.
Ability to independently own complex systems from design through production operation.
Comfortable working in a fast-moving environment where architecture and processes are being established.
Experience with GPU scheduling technologies such as Slurm, Kubernetes device plugins, NVIDIA GPU Operator, or similar frameworks is preferred.
Experience supporting AI infrastructure, machine learning platforms, HPC environments, or GPU cloud providers is preferred.
Background building multi-tenant infrastructure platforms for cloud providers or large-scale compute environments is preferred.
Experience with infrastructure automation, Infrastructure as Code, and platform engineering practices is preferred.
Familiarity with high-performance networking and GPU cluster architectures is preferred.

Benefits

Comp & perks

Competitive base pay for Bellevue market
Certain roles are eligible for additional rewards, including merit increases, annual bonus, and stock. These awards are allocated based on individual performance
U.S. based employees have access to medical, dental, and vision insurance, a 401(k) plan and company match, employees also receive per calendar year, paid holidays.