AI Infrastructure Engineer

Job Title: AI Infrastructure Engineer (Nutanix AI Platform)

Location: San Jose, CA (Hybrid/Onsite Preferred)

Duration: 12 months+ Contract

Experience: 10+ Years
Rate: Negotiable

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Position Overview

We are seeking a highly experienced AI Infrastructure Engineer to architect, deploy and optimize enterprise-scale AI infrastructure solutions leveraging the Nutanix ecosystem. The ideal candidate will have deep expertise in Nutanix Cloud Infrastructure (NCI), AOS/AHV, Nutanix Kubernetes Platform (NKP), GPU-accelerated computing and hybrid cloud environments.

This role focuses on building scalable, high-performance infrastructure that supports Large Language Models (LLMs), Generative AI workloads, AI training and AI inference platforms across on-premises and cloud environments.

The selected candidate will serve as a Subject Matter Expert (SME) for Nutanix AI infrastructure and will work closely with architecture, cloud, platform, networking and security teams.

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Required Skills (Must Have)

Nutanix Platform Expertise

• Strong hands-on experience with:

  • Nutanix Cloud Infrastructure (NCI)

  • Nutanix AOS (Acropolis Operating System)

  • Nutanix AHV (Acropolis Hypervisor)

  • Nutanix Cloud Manager (NCM)

  • Nutanix Flow

  • Nutanix Objects and Files

Kubernetes & Container Platforms

• Extensive experience with:

  • Nutanix Kubernetes Platform (NKP)

  • Kubernetes cluster deployment and administration

  • Container orchestration and workload management

  • AI/ML workload deployment in Kubernetes environments

GPU & AI Infrastructure

• Experience designing and managing GPU-enabled environments

• Hands-on experience with:

  • NVIDIA GPU ecosystem (A100, H100, CUDA, GPU Passthrough, vGPU)

  • AMD GPU ecosystem

• Experience supporting AI model training and inference workloads

Infrastructure Automation

• Terraform

• Infrastructure as Code (IaC)

• Nutanix Calm

• Automated provisioning and lifecycle management

Monitoring & Observability

• Prometheus

• Grafana

• ELK Stack

• OpenTelemetry

• Monitoring, logging, alerting and performance tuning

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Key Responsibilities

AI Infrastructure Architecture

• Design and implement scalable AI infrastructure platforms using Nutanix technologies.

• Build optimized environments supporting Generative AI, LLM training and inference workloads.

• Design high-performance compute, storage and networking architectures for AI applications.

Hybrid Cloud & Multicloud Solutions

• Architect hybrid cloud solutions leveraging Nutanix Cloud Clusters (NC2).

• Enable seamless workload portability between on-premises environments and public cloud platforms.

• Support cloud bursting and dynamic workload scaling.

Kubernetes Platform Engineering

• Deploy, manage and optimize AI workloads on Nutanix Kubernetes Platform (NKP).

• Design highly available and resilient containerized environments.

• Implement workload automation and orchestration best practices.

Storage & Data Services

• Design high-performance storage solutions using Nutanix Objects and Nutanix Files.

• Optimize storage architectures for AI/ML datasets and model repositories.

• Ensure data availability, scalability and performance.

Security & Networking

• Implement Zero-Trust security principles.

• Utilize Nutanix Flow for micro-segmentation and workload security.

• Collaborate with security and networking teams to protect sensitive AI data.

Performance Optimization

• Optimize GPU utilization and AI infrastructure performance.

• Configure GPU Passthrough and vGPU environments.

• Improve resource efficiency, scalability and operational costs.

Observability & Reliability

• Establish enterprise monitoring, logging and alerting frameworks.

• Ensure high availability, disaster recovery and fault tolerance.

• Perform root cause analysis and capacity planning.

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Preferred Qualifications

• Experience supporting AI/ML platforms, LLMs and Generative AI initiatives.

• Experience with AI model serving frameworks and inference platforms.

• Knowledge of MLOps, AI platform engineering and data pipelines.

• Experience working in enterprise-scale hybrid cloud environments.

• Nutanix certifications highly preferred.

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Required Experience

• 10+ years of Infrastructure, Cloud, Platform Engineering, or Architecture experience.

• Strong enterprise-level Nutanix experience.

• Experience supporting Kubernetes-based production environments.

• Experience with GPU-enabled infrastructure and AI workloads.