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SHI International Corp. · 3 weeks ago

Principal Architect - AI & Datacenter

Somerset, NJ USA

Full-time

Onsite

Lead/Staff

$200K/yr - $750K/yr

15+ years exp

SHI International Corp. is a global provider of IT solutions and services, and they are seeking a Principal Architect - AI & Datacenter. The role involves serving as the senior-most technical advisor in AI-driven architectures and enterprise-scale compute, storage solutions, leading strategic initiatives, and guiding teams to deliver transformative outcomes for clients.

HardwareInformation TechnologySoftware

Responsibilities

Lead Complex AI Infrastructure Pursuits: Serve as the chief architect and trusted technical strategist for multimillion-dollar AI and datacenter modernization opportunities, ensuring performance, scalability, and security alignment with enterprise goals

Architect Advanced Compute Environments: Optimize end-to-end infrastructure—GPU clusters, fabric interconnects, and AI-optimized storage—for large model training and inference workloads across on-prem, edge, and cloud platforms

Drive Strategic Customer Engagement: Co-develop digital transformation roadmaps with executive clients, emphasizing AI-ready datacenter evolution, sustainable energy efficiency, and workload orchestration

Integrate Hybrid Cloud and AI Platforms: Design architectures leveraging NVIDIA DGX, HPE GreenLake, Dell APEX, or Red Hat OpenShift AI ecosystems to ensure seamless data mobility, workload elasticity, and cost-effective scaling

Lead Proof-of-Concept and Benchmarking: Direct technical validation for AI workloads, including multi-tenant GPU performance testing, model training simulations, and inferencing benchmark optimization

Influence Product and R&D Direction: Collaborate with infrastructure engineering, software development, and AI solution groups and OEM Partners to align field innovations with datacenter roadmap investments

Mentor Next-Generation Architects: Build AI competency frameworks, train presales engineers in AI workload modeling, and elevate organizational acumen for data-driven presales execution

Provide Thought Leadership: Attend SHI and Partner events as well as webinars providing relevant content in speaking roles. Attend partner meetings in an advisory capacity. Publish articles and blogs on SHI capabilities, industry innovations and trends

Qualification

AI architecture designHybrid cloud integrationGPU clusters optimizationMLOps practicesAI frameworks knowledgeDatacenter solution designContainer orchestrationAdvanced communicationAnalytical thinkingCustomer-centric mindsetLeadershipProblem-solvingInterpersonal skills

Required

Completed Bachelor's Degree in Computer Engineering, Data Science, or related field

15+ years of experience in enterprise architecture, presales engineering, or datacenter solution design, including 5+ years dedicated to AI infrastructure or HPC systems

Strong understanding of AI frameworks (TensorFlow, PyTorch, Triton Inference Server) and MLOps integration across hybrid infrastructures

Proven experience designing and delivering large-scale AI/ML clusters, GPU cloud architectures, and fiber-connected computing fabrics

Advanced communication and executive-level advisory skills with the ability to articulate complex technical strategies in business value terms

Deep expertise in at least two domains: GPU/accelerator computing, Data fabric design, Container orchestration, Power-efficient datacenter design

Ability to travel 25%

Ability to design, implement, and configure robust AI solutions, ensuring alignment with strategic objectives and technical specifications

Ability to design comprehensive AI system structures and frameworks to meet complex requirements

The ability to design, implement, and support multi-tier applications and cloud-based architectures to meet organizational needs

Demonstrates a working knowledge of current and evolving technologies including Cloud, Data Center, Storage, and Networking

Ability to oversee and direct projects to completion, ensuring goals are met, resources are utilized efficiently, and stakeholders are satisfied

The ability to understand and manage various infrastructure components (firewalls, load balancers, hypervisors, storage, monitoring, security) and use orchestration tools to develop comprehensive technical solutions

The ability to write, debug, and maintain code in various scripting and programming languages to automate tasks and develop software solutions, specifically Python, Java, or C++

Knowledgeable in MLOps practices and tools to enhance AI model deployment and operations