出海雷达

解决方案架构师 (机架集成与数据中心计算) (远程,美国,远程)

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

开发工程市场运营限定地区(需当地身份)
公司Computacenter
薪资$170,000 - $200,000/年
工作地点United States
地域资格限定地区(需当地身份)
时区要求日间重叠约 9 小时,基本正常作息
用工类型Full Time
发布时间11 天前
数据来源Himalayas
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注意地域限制:该职位明确限定在 United States 招聘。如果你是位于中国大陆的求职者,通常需要当地工作身份才能投递,或需与雇主确认是否接受独立合同(Contractor)形式合作。

职位描述
该职位是面向客户的解决方案架构师,专注于机架集成与数据中心计算,负责为大规模AI数据中心部署设计和实现机架级别的计算基础设施。该职位将服务器、GPU、存储、网络、电源、冷却、机架设计、工厂集成和现场部署需求整合成完整的可执行方案。理想的候选人需具备深厚的计算和数据中心基础设施专业知识,同时拥有机架集成和制造流程的实际经验。该职位将与客户、解决方案专家、原始设备制造商(OEM)、工程团队、专业服务团队、集成中心、供应链、项目管理及现场交付团队紧密合作。
年度薪酬:17万美元 - 20万美元 + 奖金
你将负责的工作

  • 领导AI计算和机架集成机会的技术调研和解决方案架构。
  • 将客户的GPU、服务器、存储、网络、电源、冷却和部署需求转化为标准化的机架级设计。
  • 开发并验证机架架构、机架高度图、物料清单(BOM)、组件布局、电源需求、网络连接和集成规范。
  • 为GPU和加速计算平台、高密度AI机架、传统计算平台、存储和支持基础设施设计解决方案。
  • 定义机架集成工作流程,包括接收、准备、组装、安装、布线、配置、固件、烧机、测试、质量保证/质量控制(QA/QC)、包装和运输。
  • 与计算、网络、存储、电源、冷却、机架和集成原始设备制造商(OEM)合作,验证兼容性和技术要求。
  • 支持高密度和液冷机架设计,包括冷却分配单元(CDU)接口、集管、电源分配、重量、空间和设施依赖关系。
  • 制定可重复使用的机架构建标准和黄金配置,可在大型AI数据中心项目中扩展。
  • 支持报价请求(RFQ)/招标文件(RFP)、提案、工作说明书、技术演示、客户研讨会和设计评审。
  • 与集成中心和现场交付团队合作,确保设计方案在大规模下可制造、可部署、可测试和可支持。
  • 定义验收标准、验证计划、文档标准和设计到交付的交接要求。
  • 识别自动化物料清单(BOM)创建、机架设计、配置、验证、测试和部署文档的机会。
查看英文原文

About the role
The Solution Architect – Rack Integration & DC Compute, AI Data Center is a customer-facing technical role responsible for architecting and operationalizing rack-level compute infrastructure for large-scale AI data center deployments. The role connects server, GPU, storage, networking, power, cooling, rack design, factory integration, and onsite deployment requirements into a complete, executable solution. The ideal candidate combines deep compute and data center infrastructure expertise with hands-on knowledge of rack integration and manufacturing processes. The role works closely with customers, Solution Specialists, OEMs, engineering, Professional Services, integration centers, supply chain, project management, and field delivery teams.
Annual compensation: $170K - $200K + bonus
What you'll be doing

  • 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 you have

  • 7+ years of experience in data center compute, converged infrastructure, systems engineering, solution architecture, rack integration, or related infrastructure roles.
  • Strong background in one or more 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.
  • Experience with large-scale rack build, factory integration, staging, configuration, test, QA/QC, and deployment processes is strongly preferred.
  • Experience with AI CSPs, hyperscalers, NCPs, HPC environments, large data center operators, or major compute OEMs is highly desirable.
  • Understanding of high-density power and liquid cooling requirements associated with 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.
  • 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.
  • 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
  • Compute Architecture – Deep understanding of server, GPU, storage, networking, and integrated data center compute platforms.
  • Rack Integration – Understands how to convert a technical architecture into a repeatable physical rack build and integration process.
  • AI Infrastructure Knowledge – Understands the density, performance, power, cooling, connectivity, and operational requirements of AI compute environments.
  • Design for Scale – Creates standardized architectures and golden configurations that can be replicated across hundreds or thousands of racks.
  • Technical Problem Solving – Can troubleshoot complex issues across hardware, firmware, networking, storage, power, cooling, and physical integration.
  • Design-to-Delivery Thinking – Architects solutions with manufacturing, logistics, deployment, testing, field installation, and lifecycle support in mind.
  • Customer Engagement – Leads technical discovery, architecture workshops, solution reviews, and executive-level technical discussions.
  • Cross-Functional Leadership – Connects customer requirements with OEMs, engineering, integration centers, sourcing, Professional Services, and field delivery.
  • Quality, accuracy, and scalability of AI compute and rack integration designs
  • Speed from customer requirements to an executable rack architecture and BOM
  • Standardization and repeatability of rack designs and integration processes
  • Reduction in integration defects, field changes, rework, and deployment issues
  • Successful technical support of AI Data Center pursuits and customer programs
  • Accuracy of BOMs, rack elevations, build documentation, and configuration standards
  • Successful transition from solution architecture through integration and onsite deployment
  • Customer and OEM confidence in the technical solution
  • Continuous improvement and automation of rack integration methodology

The ideal candidate is a highly technical data center compute architect who understands both the logical architecture of AI infrastructure and the physical realities of building it at rack scale. They should be able to work from a customer's compute and GPU requirements down through server configuration, rack layout, networking, power, cooling, firmware, cabling, integration, testing, and deployment. A profile similar to the current role combines AI solution architecture with deep prior experience in compute, converged/hyperconverged infrastructure, engineering, and hands-on infrastructure design. The strongest candidates will be builders who can turn complex AI platform requirements into standardized, factory-integrated solutions that can be deployed rapidly and consistently at scale.
What you can expect
There’s so much more to enjoy about being at Computacenter than just having a rewarding career. In addition to offering competitive compensation plans and long-term career opportunities, we provide an attractive mix of benefit plans to contribute to your good health, future financial security, and peace of mind.
About us
Computacenter is a leading independent technology partner, trusted by large corporate and public sector organizations. We help our world-renowned customers to source, transform, and manage their IT infrastructure to deliver digital transformation, enabling users and their business. We’re a public company quoted on the London FTSE 250 (CCC.L) and employ over 21,000 people worldwide. In the US, we support some of the country’s best-known businesses with regional hubs in San Francisco and Irvine, CA; Norcross, GA; Plano, TX; and New York City; and Integration Centers in Silicon Valley and Atlanta.
Originally posted on Himalayas

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