Data Center Controls Network Engineer in United States

About the Team The compute infrastructure team runs the GPU fleet and large-scale compute clusters that serve the models backing ChatGPT and the API, while also supporting training workloads for our next generation models. We operate a large, modern GPU fleet and provide a unified platform for other OpenAI teams to seamlessly run production Applied AI and Research training workloads. We seek to learn from deployment and distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. Safety is more important to us than unfettered growth. About the Role You’ll own the hands-on and automation work that brings WAN, fiber, carrier, and cloud-interconnect circuits into service. Partner with network engineers, fiber providers, cloud service providers, colocation teams, and data-center technicians to move each connection from ordered and patched to verified, stable, and ready for handoff. You’ll own Layer 1 troubleshooting and circuit bring-up while building workflows that translate reliable system or model output into precise, approved technician actions, capture field feedback, and drive each connection to a green-port handoff. The right person combines strong physical-networking judgment with practical automation skills: patch-panel and port mappings, optics and light levels, provider coordination, structured operational data, API or scripting workflows, and human-in-the-loop LLM tooling. Responsibilities Own Layer 1 activation and restoration for carrier circuits, dark fiber, wavelengths, Ethernet handoffs, and dedicated cloud interconnects across data centers and points of presence. Reconcile complete A-side/Z-side as-builts: circuit IDs, LOAs/CFAs, carrier demarcations, MMR/ODF/MDF and patch-panel positions, fiber pairs, cross-connects, optics, and device ports. Investigate no-light, low-light, wrong-port, link-flap, and error-rate issues across providers and CSPs; isolate continuity, dirty connectors, polarity, incorrect patching

About the Team The Finance Platform & Technology team at OpenAI builds and scales the future-proof systems and data architecture that power our core financial operations. We enable business agility, compliance, and operational excellence across quote-to-cash, procure-to-pay, inventory, and asset management for both B2B and B2C. Our focus is on modernizing workflows through strategic integrations, scalable automation, and seamless data flows empowering smarter decisions, reliable reporting, and sustainable growth as OpenAI evolves About the Role We are looking for a Supply Chain Transformation Architect to redesign and modernize our end-to-end supply chain operations supporting robotics, consumer hardware, and data center infrastructure. This role sits at the intersection of process, systems, and data. Your primary focus will be transforming supply chain processes across planning, procurement, manufacturing, logistics, and fulfillment—then enabling those processes with the right systems architecture, data foundation, and AI-driven automation. You will help move the organization from manual, reactive operations to intelligent, data-driven supply chain execution. In this role you will: Lead End-to-End Supply Chain Transformation Evaluate and redesign core supply chain processes across demand planning, supply planning, procurement, manufacturing operations, logistics, and fulfillment. Identify operational bottlenecks, fragmented workflows, and manual processes that limit scalability. Build standardized process frameworks and operating models that support rapid scaling of hardware programs. Drive Operational Excellence Implement structured supply chain practices such as: S&OP / Integrated Business Planning Supply risk management Inventory optimization Supplier collaboration frameworks Logistics visibility and execution models Establish operational KPIs and governance to improve predictability, responsiveness, and resilience. Architect the Digital Supply Chain Tra

About the Team The Stargate team is responsible for building the physical infrastructure that powers large-scale AI systems. We design and deliver next-generation data centers optimized for dense compute clusters, advanced networking, and rapidly evolving hardware platforms. This work sits at the intersection of hardware engineering, systems architecture, and infrastructure execution—translating cutting-edge compute roadmaps into scalable, production-ready environments. Our teams partner across silicon vendors, server and storage OEMs, networking teams, and data center engineering organizations to bring new capacity online quickly, reliably, and at global scale. About the Role We are seeking a CPU & Storage Technical Lead to define and drive the server compute and storage architecture strategy for Stargate infrastructure. In this role, you will own technical direction across CPU platforms, memory configurations, local and disaggregated storage systems, and their integration into large-scale AI clusters. You will evaluate vendor roadmaps, lead platform tradeoff decisions, and ensure compute and storage systems are optimized for training, inference, and supporting services. You will work cross-functionally with hardware engineering, performance modeling, networking, supply chain, and deployment teams, as well as external partners such as AMD, Intel, OEMs, ODMs, and storage vendors. This is a highly strategic role for someone who can operate deeply at the component level while also driving long-range infrastructure decisions. Key Responsibilities Own CPU and storage technical strategy for Stargate compute infrastructure across current and future generations. Evaluate CPU platforms across performance, efficiency, memory bandwidth, PCIe topology, cost, and roadmap alignment. Define storage architectures for AI environments, including boot media, local NVMe, shared storage, caching tiers, metadata services, and high-performance data pipelines. Drive server platform de

We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time. Position Summary We are seeking an accomplished Principal Cloud Storage Engineer to lead the design, engineering, and evolution of our private cloud storage platforms. This role will focus on large-scale storage architecture, data protection, cyber recovery, and resiliency technologies across complex enterprise environments. The ideal candidate will combine deep technical expertise in storage systems with strong leadership, architectural vision, and the ability to influence technical direction across the organization. Key Responsibilities Architect and engineer enterprise storage platforms that ensure data integrity, availability, security, and disaster recovery readiness Design and implement end-to-end storage solutions, including Software Defined Storage, SAN, NAS, and object storage across private cloud and data center environments Drive strategic technology decisions by evaluating emerging products, tools, and standards supporting storage, data protection, cloud, and compute platforms Lead infrastructure initiatives involving storage modernization, data protection, cyber recovery, data migration, and resilience engineering Develop and execute enterprise strategies for backup, recovery, cyber vaulting, and business continuity Create and maintain comprehensive documentation of storage architectures, configurations, policies, and operation

We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time. Position Summary CVS Health is seeking a highly skilled and visionary Sr. Manager to lead and manage our enterprise Cisco Application Centric Infrastructure (ACI) environment and the transition to Cisco Nexus Dashboard Fabric Controller (NDFC). This role sits within the Network Engineering team and is pivotal to driving the modernization and scalability of our next-generation data center fabric. This role will help set and drive the network technology strategy for ISTS, ensuring that ISTS delivers on our mission to transform technology and provide an agile, cost optimized and resilient set of network infrastructure services to meet the evolving needs of all the CVS Health lines of business. The ideal candidate will have experience supporting complex enterprise network environments and demonstrate deep expertise in Cisco ACI and NDFC technologies. As a strategic leader, you will be responsible for setting the direction, leading a team of engineers, and ensuring the operational integrity, performance, and evolution of our fabric-based data center architecture. This position will also mentor staff members in an effort to develop excellent enterprise networking skills. Key Responsibilities Lead the deployment, administration, and lifecycle management of the Cisco ACI environment Oversee the strategic transition to and ongoing management of the Cisco

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. At Micron, we are transforming how the world uses information to enrich life. The High Bandwidth Memory (HBM) Design team develops industry-leading memory solutions that enable advances in Artificial Intelligence, high-performance computing, graphics, and data-center applications. Our engineers collaborate across global teams to deliver innovative memory architectures and semiconductor technologies that power next-generation computing systems. As an HBM Design Engineer Intern, you will work alongside experienced memory engineers and gain hands-on experience in semiconductor design, simulation, verification, and analysis. This internship provides exposure to industry-standard design methodologies, EDA tools, and cross-functional collaboration throughout the product development lifecycle. You will also have opportunities to apply AI-Assisted and AI-Enabled workflows to improve engineering productivity, debug efficiency, and design quality. Responsibilities Assist with the design, simulation, analysis, and verification of HBM memory and logic circuits using industry-standard semiconductor design tools. Support RTL development, circuit implementation, timing analysis, power analysis, and functional validation activities. Develop scripts, automation solutions, and AI-Assisted workflows to improve design productivity, debug efficiency, and design-flow quality. Collaborate with Design, Verification, Physical Design, CAD, and Product Engineering teams on technical reviews, debug activities, and project deliv

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. At Micron, we are transforming how the world uses information to enrich life. The High Bandwidth Memory (HBM) Design team develops industry-leading memory solutions that enable advances in Artificial Intelligence, high-performance computing, graphics, and data-center applications. Our engineers collaborate across global teams to deliver innovative memory architectures and semiconductor technologies that power next-generation computing systems. As an HBM Design Engineer Intern, you will work alongside experienced memory engineers and gain hands-on experience in semiconductor design, simulation, verification, and analysis. This internship provides exposure to industry-standard design methodologies, EDA tools, and cross-functional collaboration throughout the product development lifecycle. You will also have opportunities to apply AI-Assisted and AI-Enabled workflows to improve engineering productivity, debug efficiency, and design quality. Responsibilities Assist with the design, simulation, analysis, and verification of HBM memory and logic circuits using industry-standard semiconductor design tools. Support RTL development, circuit implementation, timing analysis, power analysis, and functional validation activities. Develop scripts, automation solutions, and AI-Assisted workflows to improve design productivity, debug efficiency, and design-flow quality. Collaborate with Design, Verification, Physical Design, CAD, and Product Engineering teams on technical reviews, debug activities, and project deliv

We are seeking a highly skilled and hard-working Senior Test Developer / test engineer to join our multifaceted Enterprise Software QA team. This role offers an outstanding opportunity to leave your mark on the design, construction, optimization and testing of large-scale infrastructure for various foundational NVIDIA unified cloud services and data center offerings. If you are a dedicated engineer with strong expertise in cloud infrastructure and distributed systems and want to apply your skills with AI tools, this role could fit you perfectly. You will thrive in an exciting, innovative environment. What you'll be doing: Work with development teams on test plans for all layers of SW stack for cloud infrastructure, execution, reviews, failure analysis and assessing overall quality and risk. Work with customer PMs on software issues including technical feedback from OEMs and CSPs. Develop key benchmarks to track execution and deploy process improvements to improve efficiency Leverage AI skills to expedite the test scope, test plan, execution and automation workflows. Lead NVIDIA Cloud and Data Center bring up activities which will involve validation, reporting, working with engineering to debug issues, providing design input at times, adding coverage in different areas. Design, develop and maintain CI/CD pipelines for continuous testing in cloud environments when needed. Perform performance, scalability, and reliability testing of cloud services. Implement and maintain test environments in cloud platforms such as AWS, Azure, or Google Cloud. Supervise the infrastructure to alert on significant events, ensuring the highest level of system performance and reliability. Work with various different partner teams to ensure availability of clusters to test on and take the lead in resolve all issues. Working with tea

Customer Quality & RMA Engineer Job Description POSITION OVERVIEW COMPANY OVERVIEW Infinitum Electric is a technology company pioneering the next generation of axial flux electric motors — lighter, more efficient, and more sustainable than conventional motor designs. Our motors are deployed in mission-critical applications for leading customers including hyperscale data center operators and industrial OEMs. As we scale rapidly in revenue, our Quality function is the backbone of customer trust and product integrity. POSITION SUMMARY The Customer Quality & RMA Engineer serves as the primary technical interface between Infinitum and its customers on all quality-related matters — including field complaints, warranty returns, RMA processing, corrective action management, and customer-facing quality reporting. This role owns the complete RMA lifecycle from customer notification through root cause resolution and verified closure, and is responsible for ensuring that every customer quality event is investigated with rigor, communicated with transparency, and resolved permanently. KEY RESPONSIBILITIES RMA Management & Field Complaint Resolution Own the end-to-end RMA process — from initial customer notification through receipt, inspection, root cause analysis, corrective action, and verified closure Triage and prioritize incoming field complaints and warranty returns based on customer impact, failure mode severity, and strategic account importance Conduct or coordinate physical inspection and failure analysis of returned motors and assemblies Maintain accurate, real-time RMA tracking data including cycle time, failure mode distribution, and cohort maturity trends Communicate RMA status, findings, and corrective actions to customers in a professional, timely, and technically credible manner Drive RMA rate reduction through systemic root cause analysis and closed-loop corrective action — targeting the structural elimination of recurring failure modes Custome

Job Details: Job Description: The Role and Impact As a GPU Platform Hardware Design Engineer, you will play a pivotal role in designing and developing high-quality GPU hardware platforms that drive innovation in high-performance computing, graphics, and visualization technologies. You will lead the design process from initial feasibility studies through board layout, tapeout, and platform power-on, ensuring robust functionality and compatibility with industry standards. Your expertise in platform-level requirements, electrical engineering applications, and system bring-up will directly contribute to delivering cutting-edge GPU systems that accelerate Intel's leadership in computing. Business group The Data Center Group (DCG) is dedicated to advancing Intel's role in powering the digital world with leading-edge technologies. Focused on delivering innovative solutions for data center and cloud environments, DCG supports high-performance computing and graphics to enable capabilities such as AI, machine learning, and advanced visualizations. As part of the GPU IP Engineering team within DCG, you'll contribute to developing GPU systems that meet the evolving demands of the industry while supporting Intel's broader mission to create world-changing technology. Key Responsibilities - Design, develop, and evaluate electronic components, PCBs, and integrated circuits for GPU hardware platforms. - Translate platform-level requirements into detailed specifications and ensure adherence throughout the design process. - Define component placement and trace routing rules to optimize board layouts for performance, power, and signal integrity. - Conduct feasibility studies, board layout, tapeout, and platform power-on activities. - Perform functionality tests and utilize tools to verify platform configurations and compatibility. - Research, develop, and validate firmware, hardwa

NVIDIA is transforming how the world uses AI, cloud, and accelerated computing, and trust is at the center of that mission. Our Attestation and Trust Services team builds the secure cloud services that show customers their NVIDIA platforms are healthy, resilient, and ready for their most important workloads. In this role, you help design and run services that sit at the intersection of hardware, security, and large-scale distributed systems. We partner closely with security, silicon, platform, and cloud teams to bring new ideas into reliable production services that people rely on every day. We care about building systems that last, supporting each other, and creating space for learning and experimentation. If you enjoy solving complex problems, keeping services running smoothly, and collaborating with teammates from many disciplines, we would love to talk with you! What you’ll be doing: Your main focus will be on building and managing our core attestation cloud services. Day-to-day responsibilities include crafting APIs and integrations, boosting reliability, and working alongside NVIDIA teams to convert hardware trust mechanisms and standards into production-ready solutions. You will contribute significantly to shaping how customers verify that NVIDIA platforms are secure and prepared for their workloads. Crafting and evolving attestation cloud services, APIs, and SDK/CLI integration points that confirm the integrity of NVIDIA platforms across data center, AI, networking, and partner environments. Improving reliability and operational maturity through SLOs/SLIs, alerting, runbooks, incident response, and safe rollout practices. Crafting resilient service behavior that handles dependency failures, caching challenges, regional issues, customer-side resilience needs, and graceful degradation. Architecting trust-material distribution for certificate status, re

About us Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore enjoys a culture of continuous learning and constant innovation. Job Summary We are seeking a Senior Principal Network Engineer to help design, deploy, and optimize next‑generation AI data center networks. AI training and inference workloads require extremely high bandwidth, deterministic low latency, and zero‑packet‑loss networking environments. In this role, you will partner closely with the Network Architecture Lead to design and scale high‑performance computing (HPC) network fabrics supporting GPU clusters. You will work across hardware, networking, and AI application layers to ensure Graphcore’s large‑scale AI infrastructure operates at peak performance. The ideal candidate brings deep experience operating hyperscale or HPC data center networks and has expertise in high‑speed Ethernet fabrics, RDMA technologies, advanced automation, and telemetry systems. The Team The Data Center Network Engineering team designs and operates the high‑performance network fabrics that power Graphcore’s AI compute platforms. The team collaborates closely with hardware engineering, AI researchers, and infrastructure teams to build scalable networking environments optimized for distributed training and infe

About the Team OpenAI's Industrial Compute organization builds and operates the infrastructure required to train and serve frontier AI models. The Capacity Planning team connects rapidly changing research and product demand with the compute, networking, storage, power, data center, hardware, and operational resources required to make that demand executable. About the Role We are seeking a Technical Program Manager to build and lead capacity planning across OpenAI's large-scale AI infrastructure. You will translate uncertain workload demand into clear infrastructure requirements, allocation decisions, supply commitments, activation priorities, and long-range capacity strategies. This role sits at the intersection of research, engineering, infrastructure, finance, sourcing, deployment, and operations. You will create the planning models, operating cadences, governance mechanisms, and source-of-truth systems that allow teams to understand what capacity is required, what is available, what is at risk, and what decisions must be made. This is not a finance-only forecasting or reporting role. Success requires technical fluency across the infrastructure stack, strong analytical judgment, and the ability to move consequential decisions forward when requirements, timelines, and supply conditions change quickly. Key Responsibilities Own capacity-planning processes across near-term workload allocation, quarterly execution, and longer-range infrastructure horizons. Translate research, training, inference, and product demand into compute, accelerator, cluster, networking, storage, rack, power, and site requirements. Develop scenarios that make assumptions, confidence levels, constraints, sensitivities, and decision points explicit. Reconcile requested demand against contracted, delivered, installed, activated, and workload-usable capacity. Partner with research and engineering teams to understand workload priorities, technical dependencies, utilization patterns, and changing req

About the Team OpenAI’s Hardware organization develops silicon and system-level solutions designed for the unique demands of advanced AI workloads. The team builds next-generation AI-native silicon and systems while working closely with software, research, and manufacturing partners to co-design hardware tightly integrated with AI models. In addition to delivering systems for OpenAI’s supercomputing infrastructure, the team develops the tools, methodologies, and strategic partnerships needed to accelerate hardware innovation. About the Role We’re seeking an experienced Hardware Strategic Sourcing Manager to own sourcing strategy and supplier partnerships for fiber and optical interconnect components across OpenAI’s next-generation AI infrastructure. Reporting to the Head of Partnerships & Strategic Sourcing, you will lead sourcing across fiber cable assemblies, internal optical harnesses, fiber shuffles, optical backplane assemblies, connectorized and standalone passive optical assemblies, fiber-array units (FAUs), fiber-to-chip and coupling interfaces, detachable connectors, optical routing, and assigned optical packaging, assembly, and test services. You will work closely with electrical engineering, optical engineering, systems engineering, mechanical and packaging engineering, quality, rack integration, data-center deployment,manufacturing, supply chain, finance, legal, and program management teams to translate demanding bandwidth, signal integrity, reliability, and scale requirements into resilient supplier partnerships and scalable commercial strategies. Your work will directly support the performance, reliability, manufacturability, and scale of the high-speed optical connectivity required for OpenAI’s next-generation AI systems. In this role, you will: Develop and execute a comprehensive sourcing strategy for fiber and optical interconnect components supporting high-bandwidth AI systems and infrastructure. Own sourcing across optical fiber cable assembli

About the Team OpenAI's Industrial Compute organization is building and operating the infrastructure foundation for the next generation of AI. Infrastructure Operations works across facilities, hardware, network operations, incident management, data center engineering, delivery teams, and external partners to bring capacity online safely, understand its operational state, and improve it over time. As OpenAI's data center portfolio grows across first-party and partner-delivered capacity, the organization needs clear goals, trusted data, repeatable processes, and systems that make ownership, risk, readiness, and performance visible. This role will help build the operating mechanisms that allow Infrastructure Operations to scale with rigor. About the Role We are seeking a Technical Program Manager to own the systems, data, reporting, governance, and program-management backbone for Infrastructure Operations. Reporting to the Delivery & Operations Lead, you will translate strategy into executable goals and operating cadences, turn operational needs into software and data solutions, and create the mechanisms that keep a rapidly evolving organization aligned and accountable. This role will also own the current 1P+3P delivery-tracking layer within Operations: milestones, delivery timelines, quantity forecasts, risks, decisions, and executive reporting. You will partner closely with 1P Delivery Program Management, Compute TPMs, Data Center Engineering, construction, commissioning, and operations leaders to ensure that delivery information becomes complete, usable input for readiness, handover, and ongoing operations. You will own program health and the operating system around it: the goals, data definitions, workflows, reporting, decision paths, and follow-through that help functional DRIs execute. The ideal candidate is comfortable in ambiguity, technically fluent enough to implement real systems, and relentless about converting scattered information into durable mechan