What youll do

We are seeking a Subject Matter Expert (SME) – Admin, Operate & Manage (HPE PCAI

& AI Factory Solutions) to manage and optimize HPE’s next-generation AI infrastructure platforms. The ideal candidate will have deep hands-on expertise in AI, HPC, and GPU-

accelerated environments, with solid knowledge of HPE Ezmeral, NVIDIA AI

Enterprise, Containerized workloads, and Automation frameworks. This role focuses on the operational stability, lifecycle management, and continuous improvement of large-

scale Private Cloud for AI (PCAI) and AI Factory deployments.

Key Responsibilities

1. Platform Administration •

Administer and maintain HPE PCAI and AI Factory environments, ensuring optimal uptime and performance.
- Manage compute nodes (HPE DL380a, DL325, Cray XD670), GPU clusters (NVIDIA

L40S/H100/H200), and InfiniBand NDR networks.
- Administer virtualization and container platforms such as vSphere, RHEL/RHOS,

Ezmeral Runtime Enterprise, Kubernetes, and Rancher Harvester.
- Perform configuration, patching, version upgrades, and firmware updates across

hardware and software layers.
1. Operational Monitoring & Incident Management

- Proactively monitor system health using DCGM, NetQ, Grafana, and Exivity

dashboards. • Handle alerts, performance anomalies, and incidents across GPU, network, and storage layers.
- Lead root cause analysis (RCA) and corrective action plans to prevent recurring

issues.
- Maintain operational documentation, runbooks, and incident logs.

1. Lifecycle & Configuration Management

- Manage cluster lifecycle through Ansible, AWX, HPE Performance Cluster Manager

(HPCM), and SLURM.
- Oversee automation for provisioning, scaling, and patch management of Compute and

Containerized workloads.
- Manage configuration changes, infrastructure templates, and version baselines in

production and staging environments.
1. AI Platform & Software Operations

- Operate HPE Ezmeral Unified Analytics, Data Fabric, and AI Essentials platforms.
- Support NVIDIA AI Enterprise (NVAIE) components including NIMs, NeMO

frameworks,



and RAPIDS runtime.
- Manage and monitor AI/ML workloads (LLM, NLP, Computer Vision, Chatbots) on

containerized clusters.
- Ensure smooth operation of development tools like Jupyter, Spark, Airflow, MLflow,

Kubeflow, and Ray.
1. Storage & Data Operations

- Administer VAST, WEKA, and Alletra MP storage solutions for file, object, and

distributed storage.
- Monitor storage performance, replication, and capacity utilization.
- Coordinate with storage engineering teams for performance optimization and capacity

planning.
1. Security, IAM & Compliance

- Implement and maintain Keycloak for authentication and role-based access control.
- Ensure adherence to compliance, audit, and governance standards for AI workloads.
- Support user and service account provisioning, credential management, and access

reviews.
1. Continuous Improvement & Knowledge Enablement

- Optimize automation workflows to reduce manual intervention and improve service

response time.
- Drive service health reviews, operational dashboards, and SLA compliance reporting.
- Conduct enablement sessions for L1/L2 teams and act as the final escalation point for

operational issues.
- Collaborate with HPE Engineering for patch validation, release readiness, and

operational feedback. Required Skills & Technical Expertise: Core Infrastructure Skills
- Administration of HPE DL380a, DL325, Cray XD670, and GPU-based Compute

environments.
- Strong knowledge of NVIDIA GPU stack, InfiniBand NDR, and Spectrum-X switches.
- Experience in managing VAST, WEKA, or Alletra MP storage systems. Software &

Platform Operations
- Virtualization: vSphere, RHEL, Ezmeral Runtime Enterprise
- Containers: Kubernetes,



Rancher Harvester, KubeSphere, Morpheus • Automation:

Ansible, AWX, NetBox, HPCM, SLURM
- Observability: Grafana, NetQ, Exivity, DCGM
- Security: Keycloak, IAM integrations AI/ML Platform Administration
- Experience in HPE Ezmeral Unified Analytics and Data Fabric operations
- Familiarity with NVIDIA AI Enterprise, NIMs, NeMO, and Triton Inference Server •

Working knowledge of TensorFlow, PyTorch, Spark, Kubeflow, MLflow, and Jupyter

Preferred Certifications

: • HPE ASE / Master ASE (Compute, Storage, or Ezmeral)
- NVIDIA Certified Professional / NVAIE Certification
- RHCE / Kubernetes Administrator (CKA) / VMware VCP Soft Skills:
- Strong analytical and troubleshooting capabilities.
- Excellent communication and collaboration skills across global teams.
- Ability to lead operations improvement initiatives and mentor support engineers.
- Focused on reliability, scalability, and service excellence. For Internal Job Movement:
- Approval of the employee's current manager is required.
- Employees are expected to notify their manager prior to an interview.
- Employees in Performance Improvement Plan are not eligible to apply.
- Minimum level should be EXP if applying as part of Internal Job Posting. Why Join Us:
- Work on next-generation AI infrastructure operations and automation

. • Be part of a global team managing HPE’s AI Factory and PCAI platforms supporting large-scale AI workloads.
- Opportunity to contribute to service innovation and continuous improvement initiatives

in AI infrastructure management What you need to bring:

Bachelor’s / Master’s Degree in Computer Science, IT, or equivalent field.

- 8+ years of IT infrastructure administration experience, including 3+ years in AI/HPC

or GPUbased environments.
- Proven experience in platform operations, monitoring, and lifecycle management of

enterprise-grade AI and HPC environments.
- Hands-on experience in automation and orchestration across bare metal and

containerized infrastructure.

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