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    Job · 12777096

    Talworx Solutions logo

    PCAI AI Factory

    Talworx Solutions · Bengaluru · hybrid · Posted 62d ago

    ₹25.0L - ₹40.0L PA8–13 yrsfulltimeSourced fromNaukri

    About a minute. You'll make an account on the way through.

    About this role

    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 strong 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.

    2. 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.

    3. 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.

    4. 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.

    5. 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.

    6. 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.

    7. 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.

    Sourced from naukri

    Skills

    Experience in AIExpert knowledge in HPC lustre/clusterHPC Clustering ToolsC/C++AimlHpccGPUAI/ML ModelsC plus plusinfinibandDeep LearningMachine Learning

    PCAI AI Factory · waiting for your command