HPC AI Solution Architect (S2S)

Deloitte • Tampa, FL

68d • $141,200 - $278,300

About The Position

As a Lead Cloud Integrated Infra Engineer on Deloitte’s Silicon2Service team in its AI & Engineering practice, you will design and drive deployment of integrated architectures for GPU-accelerated AI factories and high-performance computing infrastructure, partnering with Deloitte AI specialists and ecosystem partners. You will shape end-to-end solutions from discovery and reference architecture mapping through sizing and implementation. Working with sales executives, AI application specialists, delivery engineering, and managed services, you will help clients achieve measurable outcomes from private AI assets. You will lead technical solution strategy for pursuits and active opportunities, translating complex client needs into clear solutions and delivery requirements.

The Silicon to Service team delivers end-to-end AI factories and advanced technology services to help organizations build, deploy, and operate large-scale private AI and data platforms. The team supports enterprise AI adoption through private AI economics and cloud-like ease of use, working on innovative platforms and emerging technologies to solve complex enterprise problems.

The role requires an average of 50% travel, depending on work and clients. Recruiting for this role ends on 11/30/2026. The estimated salary range is $141,200 to $278,300, and the employee may also be eligible for a discretionary annual incentive program.

Requirements

• At least 8 years of experience in infrastructure architecture or engineering for large-scale platforms, including design, implementation, operations, and optimization.
• At least 4 years designing or delivering GPU-accelerated platforms for AI, ML, or high-performance computing.
• At least 3 years of Linux system administration in production environments.
• At least 3 years designing or operating distributed compute clusters for AI/HPC in hybrid cloud setups, including multi-GPU topologies, partitioning, scheduler integration, and scalability for edge-to-cloud workloads.
• At least 2 years with high-performance networking or storage for AI/HPC.
• At least 2 years building containerized platforms using Kubernetes or Red Hat OpenShift, including GPU operators/drivers, CUDA container runtime, and cluster lifecycle automation.
• At least 2 years automating infrastructure as code using tools such as Terraform and Ansible.
• At least 2 end-to-end deployments of reference architectures in the cloud or on-premises, including variants with security controls, network segmentation, operational runbooks, and validation testing.
• Experience in pre-sales or sales engineering, including discovery, solution demonstrations, and proposal/RFP contributions.
• Ability to travel an average of 50%, depending on work and the clients and industries served.

Nice To Haves

• At least 2 years implementing AI/HPC cluster scheduling with Slurm and Kubernetes, including multi-tenant queues, quotas, and GPU-aware policies.
• At least 2 years supporting generative AI infrastructure patterns, including multi-node distributed training.
• Experience with AI agents and frameworks.
• Experience with high-throughput storage for AI/HPC.
• Experience executing NVIDIA co-sell motions with OEMs such as Dell, HPC, or Lenovo; CSPs such as AWS, Azure, or Google Cloud; or independent software vendors such as Run:ai, OpenShift, or Weights & Biases.

Responsibilities

• Lead architecture for pursuits and active opportunities, including discovery, requirements, constraints, and target-state design.
• Define reference architectures for on-premises, cloud, and hybrid GPU platforms across compute, network, storage, security, software, and operations.
• Drive architecture trade-offs and decisions involving performance, scalability, reliability, locality, total cost of ownership, time-to-value, and risk.
• Own technical solution strategy in proposals and RFPs, including architecture narrative, assumptions, dependencies, sizing guidance, and delivery approach.
• Facilitate client workshops and technical reviews, translating engineering detail into executive-ready communications.
• Architect complex technology solutions focused on business outcomes, cost of quality, long-term scalability, and sustainability.
• Engage with C-suite client leadership during sales and delivery, lead technical pre-sales discussions, shape proposals, and support closing new business opportunities.
• Support go-to-market strategies through participation in industry events, conferences, and client briefings.
• Design and drive deployment of integrated GPU-accelerated AI factory and HPC architectures, from discovery and reference architecture mapping through sizing and implementation.
• Partner with Deloitte AI specialists, ecosystem partners, sales executives, AI application specialists, delivery engineering, and managed services.

Benefits

• Discretionary annual incentive program, subject to program rules and applicable factors.
• Broad range of employee benefits; specific benefits are not listed.
• Professional development opportunities, including on-the-job learning, formal development programs, leadership opportunities, and mentorship.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed