Hyperscalers And Strategic Neoclouds Lead in United States

GitLab is the intelligent orchestration platform for DevSecOps. GitLab enables organizations to increase developer productivity, improve operational efficiency, reduce security and compliance risk, and accelerate digital transformation. More than 50 million registered users and more than 50% of the Fortune 100* trust GitLab to ship better, more secure software faster. The same principles built into our products are reflected in how our team works: we embrace AI as a core productivity multiplier, with all team members expected to incorporate AI into their daily workflows to drive efficiency, innovation, and impact. GitLab is where careers accelerate, innovation flourishes, and every voice is valued. Our high-performance culture is driven by our values and continuous knowledge exchange, enabling our team members to reach their full potential while collaborating with industry leaders to solve complex problems. Co-create the future with us as we build technology that transforms how the world develops software. * Fortune 500® is a registered trademark of Fortune Media IP Limited, used under license. Claim based on GitLab data. Fortune 100 refers to the top 20% ranked companies in the 2025 Fortune 500 list, published in June 2025. Fortune and Fortune Media IP Limited are not affiliated with, and do not endorse products or services of GitLab. An overview of this role GitLab is looking for a Hyperscaler Operations Manager to join our Ecosystem Operations team. This role combines deep operational governance across GitLab's AWS and GCP partnerships with the successful execution of hyperscaler operational initiatives, serving as the operational architect of the hyperscaler GTM and the primary process owner for marketplace, co-sell, and funding operations. You will own the technology, processes, and operational infrastructure that underpin GitLab's hyperscaler motions, serving as the go-to resource for hyperscaler partners and internal teams. This role sits at the intersec

About the Team The Online Data team builds and operates the core online database and indexing services for OpenAI’s production AI applications, including supporting the explosive growth of ChatGPT, the #1 AI app in the world, and Codex, the fastest growing agentic development toolset in the world. Our mission is to ensure the reliability, correctness, and scalability of our online data stack and to curate a comprehensive portfolio of services that matches the relentless ambition of OpenAI, enabling our product and research teams to build 0-100 without getting bogged down in the minutiae of multi-region, multi-cloud, exabyte-scale data infrastructure. About the Role We are seeking an Engineering Manager to lead our Online Data Systems team, responsible for our in-house database and indexing technology. This role is about shepherding a team of world-class engineers tasked with building and operating hyperscale data storage and retrieval technology. You’ll be overseeing the delivery of extremely challenging engineering work in areas like distributed query execution, multi-region federation, self-orchestrating and self-healing services, low-level performance optimization, and more. There are few companies in the world building this kind of technology in-house at this scale where you’ll still be getting in on the ground floor. Instead of being a cog in the machine spending months chasing small optimizations, you’ll play a major part of shaping our future. In this role, you will: Build, lead, and grow high-performing infrastructure engineering teams. Drive the evolution of OpenAI’s in-house online data technologies, our core, hyper-scale database systems, indexing technologies, and vector search. Anchor delivery around measurable reliability goals (SLOs, etc) to ensure system performance and resiliency is above reproach. Champion pragmatic use of agent technology to amplify execution velocity. Reduce operational toil and incident frequency through better abstractions, gua

About the Team The Frontier Systems team at OpenAI builds, launches, and supports the largest supercomputers in the world that OpenAI uses for its most cutting edge model training. We take data center designs, turn them into real, working systems and build any software needed for running large-scale frontier model trainings. Our mission is to bring up, stabilize and keep these hyperscale supercomputers reliable and efficient during the training of the frontier models. About the Role As a Software Engineer on the Frontier Systems team focused on power management, you will work on critical infrastructure to support cutting-edge research. With large-scale supercomputers consuming substantial amounts of power, managing this efficiently is key to maximizing computational capacity. This role is critical to ensuring that our cutting-edge research supercomputing infrastructure runs smoothly, while maintaining reliability and grid-level power stability. Our team empowers strong engineers with a high degree of autonomy and ownership, as well as ability to effect change. This role will require a keen focus on system-level comprehensive investigations and the development of automated solutions. We want people who go deep on problems, investigate as thoroughly as possible, and build automation for detection and remediation at scale. In this role, you will: Develop and implement system-level and software-level solutions to optimize power usage in large-scale supercomputers, ensuring efficient and reliable operations. Build automation to monitor power consumption patterns during training workloads and design algorithms to stabilize these fluctuations, preventing issues with grid reliability. Work with researchers and engineers to design tools for real-time monitoring, detection, and remediation of power-related hardware and system faults. Collaborate cross-functionally to translate complex electrical system requirements into code, while driving continuous improvements in power man

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 a best-in-class 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 a diverse group of 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 validation lead engineer to lead at-scale rack validation efforts for next-generation AI hyperscale systems. This role focuses on post-silicon system validation across the full lifecycle, ensuring functional, electrical, and thermal performance meets product objectives. You will own end-to-end blade and rack validation including planning, development, execution, and debug while collaborating across firmware, systems, and hardware teams. The Team The Rack Validation team is responsible for ensuring system readiness and quality at scale. The team works cross-functionally with firmware, silicon, and system engineering teams to validate complex AI compute platforms. Responsibilities and Duties Lead post-silicon validation of AI compute blades and racks including test planning, development, and automation. Drive provisioning and integration of system components (SoC FW, BMC, RMC, OS) for rack-level readiness. Own execution against program achievements and report validation progress and risks. Triage test failures, collect debug data, and collaborate on root cause analysis. Track

We're looking for a Principal Engineer to join our CSP Engagements team as the technical focal point for end-to-end performance, working directly with engineering teams of key CSP/hyperscale customers to ensure they achieve various performance targets on NVIDIA platforms. In this role, you will augment NVIDIA's performance and benchmark teams with a dedicated CSP-facing focus. You will drive work streams with CSP engineering teams to build shared understanding of platform performance characteristics, gather and incorporate their workload-specific feedback into NVIDIA's optimization priorities, and validate that performance targets are met in customer-representative configurations. Your cross-CSP visibility enables you to identify patterns and drive systemic improvements in documentation, configuration guidance, and tooling. What you'll be doing: Drive performance characterization work streams with engineering teams of key CSP/hyperscale customers — ensuring they understand platform performance expectations, profiling methodology, and tuning options for their specific workloads Gather and synthesize CSP performance feedback — identify gaps between expected and actual throughput, and champion optimization priorities back into NVIDIA's CUDA, NCCL, driver, and firmware teams Ensure key open-source performance and stress tools (e.g., STREAM, GPU Burn, GPU BLAST) are updated and validated for the latest NVIDIA rack-scale systems, GPU architectures, and CPU platforms — so customers and internal teams have reliable baseline measurements from day one Work closely with CSPs to ensure their own performance and validation tooling reflects the latest GPU capabilities, memory hierarchy changes, and platform-specific tuning parameters Conduct cross-CSP performance comparison and pattern analysis — identify configuration, software, or workload differences that explai

About the Team Security is at the foundation of OpenAI’s mission to ensure that artificial general intelligence benefits all of humanity. The Security team protects OpenAI’s technology, people, and products. We are technical in what we build but are operational in how we do our work, and are committed to supporting all products and research at OpenAI. Our Security team tenets include: prioritizing for impact, enabling researchers, preparing for future transformative technologies, and engaging a robust security culture. About the Role As a Security Engineer on Detection & Response, you’ll help protect OpenAI’s most sensitive assets– including our intellectual property, customer data, and the infrastructure that supports them– by building and operating the systems we use to detect suspicious activity and respond effectively when it matters. You’ll work across endpoints, identity, cloud, hyperscale compute infrastructure, and datacenter-adjacent layers, partnering closely with security teams and infrastructure owners to define the telemetry and response requirements we need and building tooling and automation where it delivers the most leverage. In this role, you will: Build and evolve Detection & Response capabilities across OpenAI’s infrastructure, products, and research environments, with an emphasis on high-signal detection and reliable operational response. Engineer detection pipelines and tooling: develop rule lifecycle management, measurement/quality loops (coverage, precision, latency), tuning processes, and safe rollout patterns. Automate response and investigations by building workflows that reduce toil (triage, enrichment, containment, evidence capture) and improve time-to-understand/time-to-contain. Partner with other Security teams and system/infrastructure owners across the company to ensure new systems ship with the right telemetry, threat models, and response playbooks from day one. Define D&R requirements and drive visibility across endpoin

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world. NVIDIA has a rapidly expanding ecosystem of data center platform & node designs. From single node HGX/DGX systems all the way up to large multi-node NVLink domain rack architectures. These designs have become core to NVIDIA's rapidly growing enterprise and cloud provider businesses. Each bringing together the full power of NVIDIA GPUs, NVIDIA NVLink, NVIDIA InfiniBand networking, NVIDIA Grace CPUs, and a fully optimized NVIDIA AI and HPC software stack. We're searching for a highly technical, motivated manager to lead & manage the team responsible for rack-scale system software architecture. From firmware, kernel drivers, operating systems, networking, fabrics and associated user mode drivers + manageability software. You will work with component leads internally and engage with industry leading hyperscalar / cloud service providers on taking these products to market. What you’ll be doing: Drive the software end-to-end architecture for NVIDIA's rack-scale products Maintain deep understanding of the product portfolio and roadmap; translate forward-looking plans into clear, formal software requirements that anchor execution across the organization. Ensure high quality & reliable

About the Team The Hardware Health and Observability team owns the end-to-end health lifecycle of OpenAI’s global compute fleet. Our mission is to maximize healthy, usable compute across accelerator vendors, generations, cloud providers, and regions through reliable health signals, automated remediation, and scalable operational tooling. We build the systems that observe, detect, remediate, and verify hardware issues across GPUs, CPUs, networking, and platform infrastructure, enabling frontier model training and inference workloads to run reliably at hyperscale. We are the last line of defense for the success of OAI’s production and research workloads. About the Role On the Hardware Health and Observability team, you’ll build critical infrastructure that keeps OpenAI’s largest compute clusters healthy and operational at scale. Even small numbers of unhealthy systems can impact large-scale training and inference workloads. This team focuses on minimizing downtime, improving fleet efficiency, and ensuring compute resources remain continuously available to researchers and product teams. Engineers on this team own problems end-to-end, from defining health signals and debugging failures to building automated remediation systems that operate across millions of GPUs globally. In this role, you will: Define and maintain health signals across GPUs, CPUs, networking, and platform infrastructure. Build and evolve health checks that detect, remediate, and verify failures at scale. Ensure critical health checks execute with minimal latency to maximize workload uptime. Investigate hardware failures and system-level issues across large-scale compute environments. Own node lifecycle workflows including drain, quarantine, repair, RMA, and return-to-service processes. Build automation and tooling that enables global cluster management with minimal manual intervention. Partner with workload, reliability, and provider teams to integrate health signals into training and inference system

We are looking for a Senior System Software Engineer, Software Defined Networking to design, build, and operate highly performant and scalable SDN solutions for NVIDIA's AI Clouds hosting GPU-accelerated workloads — including hyperscale multi-node training, inference, cloud gaming, and cloud functions. This role spans the full lifecycle of our SDN stack — from designing and developing new control and data plane software to ensuring operational excellence in production through reliability engineering, CI/CD, observability, and incident response. What you'll be doing: Design and develop next-generation multi-tenant cloud SDN control and data plane software (OVS, OVN, OpenFlow) Build Infrastructure-as-a-Service virtual network orchestration and services using gRPC and REST to support tenant workload security and performance SLAs for BMaaS, VMaaS, and Kubernetes Drive upstream contributions to OVN-Kubernetes and related open-source projects Develop software for network observability — monitoring, telemetry, intelligent metering, and performance analysis Operate and support OVS-OVN based SDN solutions in large-scale NVIDIA AI Cloud environments Own end-to-end observability for the SDN stack — build and maintain monitoring, alerting, distributed tracing, and dashboarding to ensure real-time insight into network health, performance, and tenant SLAs Design, enhance, and maintain CI/CD pipelines (GitLab) across Linux host networking, OVS, OVN, and Kubernetes CNIs Implement GitOps approaches or related experience for secure, seamless integration with cloud infrastructure Drive reliability through incident management, resource monitoring, and performance tuning<

NVIDIA is seeking a Senior Technical Program Manager to join the CSP Engagements team, focused on deep technical engagement with hyperscale cloud service providers for NVIDIA’s next‑generation datacenter systems such as Vera Rubin NVL72. This role is intended for experienced systems and embedded software leaders—including software engineering managers, technical leads, or senior architects—who have led datacenter server and platform software programs and can operate as a trusted technical partner to hyperscale CSP engineering teams. As a member of the CSP Engagements team, you will act as the primary technical engagement leader between NVIDIA’s system software organizations and CSP platform, system software, and AI teams, ensuring alignment, readiness, and successful large‑scale deployment of NVIDIA‑based datacenter solutions. What you will be doing: Lead deep technical engagements with hyperscale CSPs as the primary NVIDIA point of contact for system software, firmware, and platform readiness for NVIDIA datacenter products. Partner directly with CSP system software, firmware, and infrastructure engineering leaders to align on software architecture, bring‑up plans, deployment readiness, and production requirements for NVIDIA‑based server and rack‑scale platforms. Represent CSP technical priorities internally, advocating for customer requirements and tradeoffs across NVIDIA’s system software, firmware, hardware, silicon, and product teams are aligned to customer needs, timelines, and constraints. Own the end‑to‑end CSP engagement lifecycle, from early technical alignment and pre‑production readiness through large‑scale deployment, escalation management, and sustained production support. Drive bi‑directional technical communication: translating CSP system‑level requirements into actionable focus areas for NVIDIA engineering teams, while clearly communicating N

About the Team OpenAI's Industrial Compute organization is building the world's most advanced AI infrastructure ecosystem. Working alongside our cloud partners, infrastructure providers, and internal engineering teams, we operate hyperscale AI campuses that support the training and deployment of frontier AI models. The Site Operations team serves as OpenAI's on-site operational presence, helping ensure campuses operate safely, efficiently, and in alignment with Industrial Compute standards. We work closely with Hardware Operations, Infrastructure Delivery, Network Operations, Security, Facilities, Construction, and our infrastructure partners to support day-to-day site execution and maintain operational readiness. As Industrial Compute continues to expand globally, Site Operations plays a critical role in ensuring each campus is prepared to support reliable AI infrastructure at scale. About the Role We are seeking a Site Operations Technician to support the daily operation of Industrial Compute campuses. This role acts as OpenAI's on-site technical representative, helping coordinate activities across hardware operations, facilities, construction, logistics, security, and external service providers. You will perform routine site inspections, support asset tracking, coordinate vendor activities, assist with operational readiness, document site conditions, and help ensure infrastructure issues are identified and resolved quickly. The ideal candidate enjoys working in highly technical environments, is detail-oriented, and thrives in fast-paced operational settings where no two days are the same. Key Responsibilities Perform routine walkthroughs of Industrial Compute facilities to verify operational readiness and identify potential issues. Monitor site conditions and report abnormalities involving hardware spaces, network rooms, utilities, logistics areas, and common infrastructure. Support coordination of vendors, contractors, and partner organizations performing work o

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. NVIDIA has a rapidly expanding ecosystem of data center platform & node designs. From single node HGX/DGX systems all the way up to large multi-node NVLink domain rack architectures. These designs have become core to NVIDIA's rapidly growing enterprise and cloud provider businesses. Each bringing together the full power of NVIDIA GPUs, NVIDIA NVLink, NVIDIA InfiniBand networking, NVIDIA Grace CPUs, and a fully optimized NVIDIA AI and HPC software stack. We're searching for a highly motivated, technical leader to drive the engineering roadmap and innovation for our rack system software architecture. From firmware, kernel drivers, operating systems, networking, fabrics and associated user mode drivers &#43; manageability software. You will work with component leads internally and engage with industry leading hyperscalar / cloud service providers on taking these products to market. What you’ll be doing: Drive the software end-to-end architecture for NVIDIA's rack-scale products Maintain deep understanding of the product portfolio and roadmap; translate forward-looking plans into clear, formal software requirements that anchor execution across the organization. Ensure high quality & reliable software; serving as a trusted architectural partner to teams requiring

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

This role will support the fleet infrastructure team at OpenAI. The fleet team focuses on running the world’s largest, most reliable, and frictionless GPU fleet to support OpenAI’s general purpose model training and deployment. Work on this team ranges from Maximizing GPUs doing useful work by building user-friendly scheduling and quota systems Running a reliable and low maintenance platform by building push-button automation for kubernetes cluster provisioning and upgrades Supporting research workflows with service frameworks and deployment systems Ensuring fast model startup times though high performance snapshot delivery across blob storage down to hardware caching Much more! About the Role As an engineer within Fleet infrastructure, you will design, write, deploy, and operate infrastructure systems for model deployment and training on one of the world’s largest GPU fleet. The scale is immense, the timelines are tight, and the organization is moving fast; this is an opportunity to shape a critical system in support of OpenAI's mission to advance AI capabilities responsibly. 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: Design, implement and operate components of our compute fleet including job scheduling, cluster management, snapshot delivery, and CI/CD systems. Interface with researchers and product teams to understand workload requirements Collaborate with hardware, infrastructure, and business teams to provide a high utilization and high reliability service You might thrive in this role if you: Have experience with hyperscale compute systems Possess strong programming skills Have experience working in public clouds (especially Azure) Have experience working in Kubernetes Execution focused mentality paired with a rigorous focus on user requirements As a bonus, have an understanding of AI/ML workloads About OpenAI OpenAI is an AI resea