Principal AI Infrastructure Architect

Government Acquisitions; United States; On-site; USD 180,000 - 280,000; Full time

Job summary

Government Acquisitions, LLC (GAI), a Computacenter company, seeks a Principal AI Infrastructure Architect to lead the technical strategy for AI infrastructure, GPU-driven environments, and enterprise AI platforms for U.S. Federal Government customers.

The role reports to the CTO and collaborates with executive leadership, sales, and partners to translate complex requirements into secure, scalable solutions. Travel may be required as needed.

Qualifications

• 15+ years in enterprise infrastructure, data center, cloud, HPC or related
• 7+ years in senior architecture or technical leadership roles
• Experience designing complex, large-scale AI/HPC environments
• Secure, resilient, and scalable AI training/inference infra
• Ability to translate mission requirements into architectures for federal customers

Responsibilities

• Serve as senior technical authority for AI infrastructure and enterprise AI platform design
• Lead architecture and strategy for AI factories, GPU environments, and large-scale AI platforms
• Develop reusable reference architectures, sizing methodologies, capacity models, and implementation frameworks for Federal AI deployments
• Design and validate GPU-based platforms for training/inference, clustering, performance optimization, and lifecycle planning
• Provide technical leadership with NVIDIA ecosystem partners; support workshops and GTM activities
• Architect high-performance storage and data solutions for AI workloads; evaluate tech for performance and security
• Define infra patterns for enterprise LLM and generative AI deployments (model hosting, RAG, secure access)
• Engage with customers, executives, proposals, and strategic pursuits to win technical engagements
• Mentor solution engineering staff; ensure quality and consistency of designs
• Evaluate emerging AI infra technologies and advise leadership on strategy and investments
• Build trusted relationships with Federal customers and ecosystem leadership

Skills

Enterprise infra

HPC & GPU

AI infrastructure

Executive communication

Customer engagement

Tools

NVIDIA DGX

NVIDIA HGX

CUDA

NVIDIA AI Enterprise

Job description

Role Summary

Government Acquisitions, LLC (GAI), a Computacenter company, is seeking a highly accomplished Principal AI Infrastructure Architect to serve as the company’s senior technical authority for AI infrastructure, accelerated computing, and enterprise AI platform architecture. This role leads the technical strategy and design of AI factories, GPU-based computing environments, large language model (LLM) platforms, and next-generation AI infrastructure for U.S. Federal Government customers. The Principal Architect works directly with executive leadership, sales, solution engineering, strategic technology partners, and customers to translate complex technical requirements into secure, scalable, mission-aligned solutions. Reports to the CTO.

Role Summary

Government Acquisitions, LLC (GAI), a Computacenter company, is seeking a highly accomplished Principal AI Infrastructure Architect to serve as the company’s senior technical authority for AI infrastructure, accelerated computing, and enterprise AI platform architecture. This role leads the technical strategy and design of AI factories, GPU-based computing environments, large language model (LLM) platforms, and next-generation AI infrastructure for U.S. Federal Government customers. The Principal Architect works directly with executive leadership, sales, solution engineering, strategic technology partners, and customers to translate complex technical requirements into secure, scalable, mission-aligned solutions. Reports to the CTO.

Key Responsibilities

• Serve as GAI’s senior technical authority for AI infrastructure, accelerated computing, GPU architectures, and enterprise AI platform design.
• Lead architecture and technical strategy for AI factories and large-scale AI environments spanning compute, storage, networking, data platforms, security, and AI software.
• Develop and maintain reusable reference architectures, design standards, sizing methodologies, capacity models, and implementation frameworks for Federal AI deployments.
• Design and validate GPU-based platforms for AI training and inference, including cluster architecture, workload placement, performance optimization, scalability, resiliency, and lifecycle planning.
• Provide technical leadership across the NVIDIA ecosystem, including DGX, HGX, NVIDIA AI Enterprise, NIM microservices, CUDA, and AI Factory architectures; support joint workshops, solution development, and go-to-market activities with NVIDIA and ecosystem partners.
• Architect high-performance storage and data solutions for AI training, inference, data lakes, hybrid AI environments, and other data-intensive workloads; evaluate technologies based on performance, scale, availability, security, and operational requirements.
• Design high-performance networking for distributed AI environments, including GPU-to-GPU communication, cluster fabrics, distributed training, large-scale inference, and AI Factory deployments.
• Define infrastructure patterns for enterprise LLM and generative AI deployments, including model hosting and serving, Retrieval-Augmented Generation (RAG), agentic AI, secure model access, and Federal on-premises, hybrid, and air-gapped environments.
• Provide technical leadership for GAI’s most strategic AI pursuits by supporting customer discovery, executive briefings, architecture workshops, capture activities, proposals, competitive positioning, solution reviews, and technical win strategies.
• Partner with Pre-Sales Solution Engineering to qualify opportunities, review complex architectures, mentor technical staff, and ensure solution quality, consistency, and technical excellence.
• Evaluate emerging AI infrastructure technologies and advise executive leadership on technical strategy, partner priorities, investments, Innovation Lab capabilities, and differentiated solution offerings.
• Build trusted-advisor relationships with Federal customers and maintain strong technical relationships with OEM, ISV, cloud, data center, and ecosystem partner leadership.

Qualifications & Experience

• 15+ years of experience in enterprise infrastructure, data center architecture, cloud, high-performance computing (HPC), or related technical domains, including 7+ years in senior architecture or technical leadership roles.
• Demonstrated experience designing complex, large-scale AI, HPC, GPU, or accelerated computing environments.
• Deep technical knowledge of GPU infrastructure, distributed computing, high-performance storage, networking, enterprise data platforms, and hybrid cloud architectures.
• Experience designing secure, resilient, and scalable infrastructure for AI training, inference, generative AI, LLM, RAG, or agentic AI workloads.
• Proven ability to lead complex technical engagements with executive-level customers and translate mission and business requirements into actionable architectures.
• Strong communication, presentation, documentation, and customer-facing skills, with the ability to explain advanced technical concepts to both technical and non-technical audiences.
• Experience supporting U.S. Federal Government customers and familiarity with Federal security, compliance, acquisition, and mission requirements.
• Ability and willingness to travel for customer engagements, technical workshops, partner activities, and strategic pursuits as required.

Preferred Qualifications

• Hands-on architecture experience with NVIDIA DGX, HGX, NVIDIA AI Enterprise, NIM, CUDA, and AI Factory solutions.
• Experience supporting Department of Defense, Intelligence Community, and/or Civilian Federal agencies.
• Experience architecting solutions using technologies from NVIDIA, Dell Technologies, HPE, Cisco, VAST Data, WEKA, Pure Storage, NetApp, Microsoft Azure, AWS, or comparable enterprise platforms.
• Experience with enterprise generative AI, machine learning, LLM serving, RAG, containerized AI platforms, Kubernetes, and model lifecycle infrastructure.
• Active U.S. Government security clearance or ability to obtain and maintain a clearance.

Measures of Success

Quality, scalability, security, and repeatability of AI infrastructure architectures; adoption of reference designs and technical standards; customer and executive confidence in GAI’s technical leadership; effectiveness of strategic pursuit and proposal support; technical win contribution and AI infrastructure pipeline influence; development and mentorship of engineering teams; and strength of joint solution development with NVIDIA and other strategic partners.

Primary Outcome

Establish GAI as a recognized technical leader in Federal AI infrastructure by translating mission requirements into secure, high-performance, multi-vendor AI architectures that accelerate customer outcomes, strengthen strategic partnerships, improve technical win rates, and enable successful deployment of enterprise AI at scale.