Solution Architect (Rack Integration & DC Compute) (Telecommuter, US)

About This Opportunity

We are representing a confidential technology infrastructure partner in their search for a Solution Architect – Rack Integration & DC Compute to support large-scale AI data center deployments across the United States. This is a remote/telecommuter role based in the US.

This customer-facing technical position requires architecting and operationalizing rack-level compute infrastructure for AI environments. You'll connect server, GPU, storage, networking, power, cooling, rack design, factory integration, and onsite deployment requirements into complete, executable solutions. The role demands deep compute and data center infrastructure expertise combined with hands-on knowledge of rack integration and manufacturing processes.

Responsibilities

• Lead technical discovery and solution architecture for AI compute and rack integration opportunities
• Translate customer GPU, server, storage, network, power, cooling, and deployment requirements into standardized rack-level designs
• Develop and validate rack architectures, rack elevations, BOMs, component placement, power requirements, network connectivity, and integration specifications
• Architect solutions for GPU and accelerated compute platforms, high-density AI racks, traditional compute platforms, storage, and supporting infrastructure
• Define rack integration workflows including receiving, kitting, assembly, installation, cabling, configuration, firmware, burn-in, testing, QA/QC, packaging, and shipment
• Partner with compute, networking, storage, power, cooling, rack, and integration OEMs to validate compatibility and technical requirements
• Support high-density and liquid-cooled rack designs, including CDU interfaces, manifolds, power distribution, weight, space, and facility dependencies
• Develop repeatable rack build standards and golden configurations that can be scaled across large AI data center programs
• Support RFQs/RFPs, proposals, statements of work, technical presentations, customer workshops, and design reviews
• Work with integration centers and field delivery teams to ensure designs are manufacturable, deployable, testable, and supportable at scale
• Define acceptance criteria, validation plans, documentation standards, and design-to-delivery handoff requirements
• Identify opportunities to automate BOM creation, rack design, configuration, validation, testing, and deployment documentation

What We're Looking For

Required Experience:

• 7+ years of experience in data center compute, converged infrastructure, systems engineering, solution architecture, rack integration, or related infrastructure roles
• Strong background in AI data center areas including GPU/accelerated compute, server platforms, converged or hyperconverged infrastructure, rack integration, high-density compute, AI/HPC infrastructure, storage, or data center networking
• Deep understanding of enterprise and data center compute platforms, including server architecture, CPU/GPU systems, memory, storage, PCIe, NICs/DPUs, firmware, and systems management
• Experience designing or supporting integrated rack solutions including compute, network, storage, PDUs, cabling, power, cooling, and mechanical requirements
• Strong customer-facing communication, technical presentation, documentation, and architecture-review skills
• Ability to work across sales, engineering, OEMs, integration operations, professional services, supply chain, project management, and field delivery

Strongly Preferred:

• Experience with large-scale rack build, factory integration, staging, configuration, test, QA/QC, and deployment processes
• Experience with AI cloud service providers, hyperscalers, HPC environments, large data center operators, or major compute OEMs
• Understanding of high-density power and liquid cooling requirements for current and next-generation AI compute platforms
• Ability to create and validate rack elevations, BOMs, build documentation, configuration standards, test plans, and implementation requirements
• Experience working with major compute and infrastructure OEMs and understanding technology roadmaps and lifecycle considerations
• Strong troubleshooting and root-cause analysis skills across integrated compute, network, storage, firmware, and physical infrastructure

Valued Technical Skills:

• NVIDIA GPU and accelerated computing platforms, including integrated AI rack architectures
• Dell Technologies, HPE, Lenovo, Supermicro, or other enterprise/AI compute platforms
• Converged and hyperconverged infrastructure
• AI/HPC clusters and large-scale GPU deployments
• High-density rack integration and factory build environments
• Liquid-cooled compute and rack-level thermal infrastructure
• 400G/800G Ethernet and InfiniBand connectivity within AI compute environments
• Enterprise and AI storage platforms
• Firmware, BIOS, BMC, systems management, configuration, and validation
• Burn-in, functional testing, L1/L2 validation, QA/QC, and rack acceptance testing
• Automation of rack design, BOMs, configuration, testing, and deployment workflows
• Multi-site deployment standards and repeatable AI infrastructure methodologies

How We Work With You

Our talent team at Get A Job.ai partners with leading organizations to place specialized professionals in critical infrastructure roles. When you apply through our platform:

• A recruiter from Get A Job.ai will review your application and conduct an initial screening
• If there's a strong match, we'll discuss the role in detail and prepare you for client interviews
• We'll submit your profile to our client and coordinate all interview stages
• Please do not contact the client directly—all communication flows through Get A Job.ai

Pay

Compensation for this position will be competitive and commensurate with experience. Details will be discussed during the screening process with our recruiting team.

Equal Employment Opportunity: Get A Job.ai is committed to fair and equitable recruiting practices. We welcome applications from all qualified candidates regardless of race, color, religion, sex, national origin, age, disability, veteran status, or any other legally protected characteristic.