Datacenter Networking Technician, AI Compute Deployment - Stargate

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

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 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 is building the infrastructure foundation for the next generation of AI. The Data Center Engineering team defines the strategy, reference architectures, technical requirements, and delivery standards for the large-scale data centers that support OpenAI research, products, and infrastructure partners. As a Data Center Controls Network Engineer, you will design, validate, and scale the controls and OT network architectures that support high-density AI data centers. You will work across controls systems, OT infrastructure, telemetry, commissioning, deployment, and operations, partnering with mechanical, electrical, IT/networking, security, and external delivery teams. About the Role We are seeking a mid to senior OT Network Engineer with a strong controls systems background to lead the design and operation of resilient, secure, and scalable OT network architectures for high-density AI data centers. This role translates compute, power, cooling, and operational requirements into practical OT network designs, evaluates vendor solutions, and drives technical decisions across controls infrastructure, telemetry, commissioning, and operations. The ideal candidate has strong hands-on experience in mission-critical OT environments, including industrial networking, virtualized infrastructure, and OT network operations, with expertise in routing, switching, segmentation, firewall policy, time synchronization, monitoring, and network lifecycle support. Key Responsibilities Define controls, automation, and OT network requirements for AI data center campuses. Develop reference architectures, engineering standards, and reusable design templates. Review and develop basis-of-design and functional design documents, including OT network diagrams, IP/VLAN schemes, telemetry architectures, data flow diagrams, and commissioning requirements. Design OT and infrastructure network architectures, including physical topology, logical topology, IP addressing, subnetting, VLA

About the Team OpenAI's Industrial Compute organization is building and scaling the infrastructure required to support frontier AI. The Infrastructure Strategic Sourcing team connects technical and project requirements to supplier readiness, contracting, purchasing, equipment delivery, and portfolio-level risk visibility across owner-furnished contractor-installed equipment (OFCI), data center networking, rack systems and integration, fiber, cabling, optical interconnects, and related infrastructure. The team partners across Pre-Construction, Design, Construction, Electrical and Mechanical Engineering, Network Engineering, Hardware and Rack Delivery, Strategic Sourcing, Procurement, Legal, Finance, Accounts Payable, Logistics, and external suppliers. We build the operating mechanisms that keep sourcing decisions, purchase execution, long-lead equipment, network and fiber dependencies, rack readiness, and delivery commitments aligned to infrastructure schedules. About the Role We are seeking an Infrastructure Sourcing Operations Lead to own procurement operations across pre-construction, design, construction, and sourcing through purchase order issuance, while maintaining visibility through invoice resolution, production, logistics, delivery, installation, and readiness. The portfolio includes electrical and mechanical OFCI, networking equipment, rack systems and integration, fiber, cabling, optical interconnects, and other infrastructure required to bring capacity online. In this role, you will set priorities, make or escalate decisions that affect cost, supplier relationships, contractual position, and delivery schedules, and define the standards used by execution support for queue management, documentation, tracker maintenance, and recurring reporting. Success requires sound commercial and program judgment, operational rigor, systems thinking, and the ability to turn incomplete information across vendors, tools, and project teams into clear decisions, accountable

About the Team OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. About the Role As an AI Accelerator Systems Software Technical Program manager at OpenAI, you will help bring our chips/system hardware roadmap to life, navigating an array of technical and partnership challenges. We’re looking for people excited to push the frontiers of computing by navigating technical explorations and are passionate about building. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Manage the end-to-end software development from design to implementation for our AI acceleration systems, working across technical, cross-functional and external stakeholders Lead planning and scheduling of AI system software designs with our strategic partners and vendors Coordinate and lead internal resources and communication for efficient interaction with partners and vendors. You might thrive in this role if you: Have experience as a software technical program manager for data center system products (server, GPU, TPU, networking, storage and so on) taking products from concept to volume in a data center environment ensuring the systems scale with high quality Know end-to-end software development program management techniques from concept, design, production, deployment into the data center Want to help design some of the world’s largest supercomputing systems, working at the edge of complex hardware challenges Enjoy working with and enabling world-clas