AI Infrastructure Consulting Engineer – Orchestration & Platform

CDW

9d•$77,725 - $108,265

About The Position

The AI Infrastructure Consulting Engineer – Orchestration & Platform Engineering implements, integrates, and supports platforms that schedule, govern, and operate enterprise AI workloads. This client-facing, billable role delivers technical outcomes and ensures solutions are implemented as designed to the client’s satisfaction and approval. The engineer works across Kubernetes-based and workload-scheduling environments to enable reliable, secure, multi-user access to accelerated computing resources. The role involves managing time and expenses against Statement of Work expectations, proactively escalating potential scope, schedule, or budget issues, and implementing AI workload orchestration, scheduling, resource governance, and platform services in customer environments. Depending on the engagement, the engineer deploys and integrates Kubernetes, Run:ai, ClearML, Slurm, NVIDIA software components, container registries, observability, and related platform services. The engineer performs platform discovery, installation, configuration, validation, upgrades, troubleshooting, and client knowledge transfer. They collaborate with security, networking, compute, storage, application, and data teams; provide technical input for project and solution planning; and maintain project documentation, configurations, test plans, work logs, and client handoff materials. The position may require work beyond regularly scheduled shifts, select weekends, overtime, and travel to CDW locations or client sites as needed.

Requirements

Bachelor’s degree and 3 years of experience delivering complex platform, infrastructure, or cloud-native solutions, including planning, implementation, integration, and support; or 7 years of such experience.
Hands-on experience administering Kubernetes or enterprise Kubernetes distributions in production or customer environments.
Experience with containers, registries, Helm, operators, storage classes, ingress, identity integration, secrets, and role-based access control.
Working knowledge of GPU scheduling, quotas, tenancy, resource allocation, job lifecycle, and utilization concepts in AI environments.
Experience with one or more workload platforms such as Run:ai, ClearML, Slurm, NVIDIA Base Command, or comparable orchestration and scheduling technologies.
Working knowledge of Linux, scripting, APIs, Git-based workflows, and infrastructure automation.
Ability to build and execute implementation and test plans aligned with project deliverables and the Statement of Work.
Strong written and verbal communication skills, including the ability to interact effectively with leadership stakeholders and clients.
Ability to create technical documentation and transfer knowledge to administrators and platform users.
Attention to detail, analytical problem-solving skills, and ability to balance competing priorities while meeting deadlines.
Ability and willingness to work beyond regularly scheduled shifts, select weekends, or overtime as needed to meet client needs.
Ability and willingness to travel as needed to CDW locations or client sites.
Valid U.S. driver’s license.

Nice To Haves

Experience integrating Kubernetes with NVIDIA GPU Operator, Network Operator, device plugins, or NVIDIA AI Enterprise components.
Experience with platform observability, policy, security, identity, MLOps, CI/CD, and infrastructure-as-code tooling.
Familiarity with Kubeflow, MLflow, Argo, GitOps, Prometheus, Grafana, or comparable ecosystem tools.
Relevant Kubernetes, NVIDIA, Linux, or automation certifications.

Responsibilities

Manage time and expenses to meet or exceed Statement of Work expectations, escalating potential scope, schedule, or budget issues promptly.
Implement and configure AI workload orchestration, scheduling, resource governance, and platform services in customer environments.
Deploy and integrate Kubernetes, Run:ai, ClearML, Slurm, NVIDIA software components, container registries, observability, and supporting platform services as applicable.
Perform platform discovery, installation, configuration, validation, upgrades, and troubleshooting.
Transfer platform knowledge to clients.
Collaborate with security, networking, compute, storage, application, and data teams to resolve cross-platform dependencies.
Provide technical input for SOWs, ROMs, LOEs, implementation plans, and solution validation when requested.
Create and maintain project documentation, as-built configurations, test plans, work logs, and client handoff materials.