The Job

Tower Lead - Red Hat Enterprise Linux, Red Hat Satellite, Red Hat Cluster

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I korthet

The AI Infrastructure Engineer (L4) is an enterprise-level architectural leadership role responsible for designing, governing, and scaling next-generation GPU/accelerator platforms for AI/ML workloads. This domain leader drives roadmap, standards, and cross-functional alignment, optimizing Linux systems and large-scale distributed training/inference architectures.

Ansvarsområden

  • Define and own end-to-end architecture for enterprise AI infrastructure platforms (GPU, storage, network, orchestration).
  • Establish reference architectures, design standards, and best practices for AI/ML platforms across hybrid/cloud environments.
  • Lead platform modernization (AI-native infrastructure, automation-first, GPUaaS models).
  • Drive platform scalability strategy for multi-cluster, multi-region deployments.
  • Optimize Linux systems (Ubuntu, RHEL, Rocky) for AI/HPC workloads through NUMA, kernel, and clock tuning.
  • Define long-term roadmap for AI infrastructure aligned with business and AI/GenAI adoption strategy.
  • Evaluate and onboard emerging GPU/accelerator technologies (NVIDIA, AMD, TPU, specialized AI hardware).
  • Lead vendor strategy and partnerships (OEMs, cloud providers, NVIDIA ecosystem, etc.).
  • Provide strategic advisory to leadership on AI infrastructure investments and scaling decisions.
  • Lead optimization of large-scale distributed training and inference architectures.
  • Establish best practices for LLM training/inference platforms (vLLM, Triton, TensorRT-LLM, DeepSpeed).

Krav

  • Bachelor’s/master’s degree in computer science, Engineering, or related field.
  • 12–18 years of overall infrastructure/platform engineering experience.
  • 6–10 years in AI/ML infrastructure and distributed systems at scale.
  • Proven experience in architecting enterprise AI platforms (on-prem + cloud + hybrid).
  • Deep expertise in Kubernetes at scale.
  • Deep expertise in GPU infrastructure (NVIDIA ecosystem).
  • Deep expertise in HPC and distributed training frameworks.
  • Strong exposure to GenAI / LLM workloads and phantomization.
  • Demonstrated experience in leading large programs.
  • Demonstrated experience in defining architecture & strategy.
  • Demonstrated experience in customer-facing solutioning.
  • Knowledge on Pacemaker and devops.
  • Linux, Pacemaker.
  • Very good understanding on Hardware, Linux operating system, performance management, network.
  • Good Knowledge on Kubernetes, Virtualization, Ansible, Red hat Satellite.
  • Knowledge on Hyperscalers like AWS/Azure/GCP.

Önskade kvalifikationer

  • NVIDIA Certified AI Infrastructure (Associate/Professional).
  • CKA / CKS (Kubernetes).
  • AWS / Azure Architect (Professional level preferred).
  • Relevant Red Hat Certifications (E.G., Red Hat Certified Engineer Rhce, Red Hat Certified Specialist In Ansible Automation) Are Optional But Valuable.

Förmåner

  • Supercharge your potential.
  • Find your career.
  • Find your spark.
  • A place that knows that helping its customers stay on top starts by putting its people first.
#AI Infrastructure#ML Infrastructure#GPU Platforms#HPC#Kubernetes#Linux#Red Hat#Satellite#Cluster#DevOps#Nvidia#Nvidia GPU#Enterprise Architecture#Scalability#Performance Optimization#GenAI#LLM
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Företag

HCLTech

Publicerade jobb

för 1 månad sedan

Anställningstyp

Heltid

Arbetsform

På plats

Erfarenhetsnivå

Ledning

Platser

Bengaluru, India

Kvalifikation

Kandidatexamen, Masterexamen

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