Ai Infrastructure Systems Engineer Jobs

About the Team OpenAI is helping build the infrastructure that powers the next generation of artificial intelligence. Through Stargate, we are developing and operating large-scale AI compute campuses that require world-class execution across data center design, construction, commissioning, and operations. The Infrastructure Operations team is responsible for bringing AI infrastructure online and ensuring it operates reliably at scale. We partner closely with hardware, network, deployment, construction, and operations teams to deliver mission-critical environments capable of supporting frontier AI workloads. As our footprint expands, operational excellence becomes increasingly important to ensuring safe, reliable, and efficient campus operations. About the Role We are seeking a Critical Facilities Manager to support the commissioning, operational readiness, and long-term operation of next-generation AI data center campuses. This role sits at the intersection of construction, commissioning, hardware deployment, and facilities operations. You will be responsible for ensuring mission-critical infrastructure is prepared to support hardware deployment, transitioned successfully into production operations, and maintained to the highest standards of reliability and availability. You will lead day-to-day operational execution across electrical, mechanical, controls, and supporting infrastructure systems while partnering closely with commissioning teams, site operators, vendors, and engineering organizations. This role requires a strong blend of technical depth, operational leadership, and cross-functional execution. Key Responsibilities Lead day-to-day operations of mission-critical facility infrastructure across AI compute campuses. Own operational readiness activities supporting new campus deployments and infrastructure expansion. Partner with commissioning teams to transition facilities from construction and startup into steady-state operations. Develop, implement, and co

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 Global Sourcing Manager – Rack & Mechanicals to lead sourcing strategy and supplier engagement for rack infrastructure and mechanical hardware components supporting Graphcore’s AI infrastructure platforms. This role partners closely with engineering, supply chain, and finance teams to secure best-in-class capacity, cost, and delivery performance for critical hardware technologies. The successful candidate will translate technical product roadmaps into sourcing strategies, negotiate complex commercial agreements, and ensure resilient supply chains supporting global infrastructure deployment. The Team The Global Sourcing Management (GSM) team defines and executes supplier strategies across Graphcore’s hardware and infrastructure ecosystem. The team works closely with engineering and supply chain functions to identify, develop, and manage suppliers that support Graphcore’s product roadmap and operational scale. Responsibilities and Duties Own strategic sourcing activities for rack and mechanical hardware components. Develop and execute multi-year commodity strategies aligned with engineering roadm

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 Global Sourcing Manager – Contract Manufacturing to help define and lead the strategic sourcing and supplier management strategy for contract manufacturing partners supporting Graphcore’s AI infrastructure platforms. This leadership role partners closely with Engineering, Product, and Executive Leadership to secure best-in-class capacity, cost, quality, and delivery performance for critical manufacturing partners and ensure supply continuity for global infrastructure deployment. The Team The Global Sourcing Management (GSM) team defines and executes supplier strategies across Graphcore’s hardware and infrastructure ecosystem. The team partners with engineering, product management, and supply chain teams to build long-term supplier relationships that support Graphcore’s technology roadmap and infrastructure growth. Responsibilities and Duties Be responsible for the end-to-end sourcing strategy for contract manufacturing partners supporting AI infrastructure platforms. Build, lead, and mentor a high-performing sourcing team. Develop and execute multi-year supplier and commodity strategies aligned wit

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 Sourcing Manager – Memory and Storage to lead strategic sourcing activities across Graphcore’s memory and storage technology portfolio supporting AI infrastructure platforms. This role will be responsible for developing sourcing strategies, managing supplier relationships, leading commercial negotiations, and ensuring long-term supply continuity across key memory and storage technologies. Working closely with Engineering, Product Management, Operations, Manufacturing, and Supply Chain teams, the successful candidate will influence technology roadmaps, supplier strategies, capacity planning, and cost optimisation initiatives while balancing quality, performance, scalability, and supply resilience requirements. The role requires a combination of strong commercial expertise, technical understanding of infrastructure technologies, and the ability to build effective partnerships across internal and external stakeholders. The Team The Global Sourcing Management (GSM) team defines and executes supplier strategies across Graphcore’s hardware and infrastructure ecosystem. The team partners closely with Engi

About the Team OpenAI is helping build the infrastructure that powers the next generation of artificial intelligence. Through Stargate, we are developing and operating large-scale AI compute campuses that require world-class execution across data center design, construction, commissioning, and operations. The Infrastructure Operations team is responsible for bringing AI infrastructure online and ensuring it operates reliably at scale. We partner closely with hardware, network, deployment, construction, and operations teams to deliver mission-critical environments capable of supporting frontier AI workloads. As our footprint expands, operational excellence becomes increasingly important to ensuring safe, reliable, and efficient campus operations. About the Role We are seeking a Facilities Operations Manager to support the commissioning, operational readiness, and long-term operation of next-generation AI data center campuses. This role sits at the intersection of construction, commissioning, hardware deployment, and facilities operations. You will be responsible for ensuring mission-critical infrastructure is prepared to support hardware deployment, transitioned successfully into production operations, and maintained to the highest standards of reliability and availability. You will lead day-to-day operational execution across electrical, mechanical, controls, and supporting infrastructure systems while partnering closely with commissioning teams, site operators, vendors, and engineering organizations. This role requires a strong blend of technical depth, operational leadership, and cross-functional execution. Key Responsibilities Lead day-to-day operations of mission-critical facility infrastructure across AI compute campuses. Own operational readiness activities supporting new campus deployments and infrastructure expansion. Partner with commissioning teams to transition facilities from construction and startup into steady-state operations. Develop, implement, and

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 Global Sourcing Director to lead supply and demand planning across Graphcore’s global operations. This role will sit at the intersection of Finance, Sales, Marketing, Engineering, and Operations to translate market demand into actionable supply chain strategies. You will drive forecasting, sourcing, inventory optimization, and operational scalability to support the rapid growth of next-generation AI infrastructure platforms. The Team The Supply Chain and Operations team is responsible for enabling Graphcore’s global product delivery and operational excellence. The team collaborates cross-functionally to manage sourcing, forecasting, inventory, and supplier engagement to ensure reliable execution across the business. Responsibilities and Duties Develop and execute end-to-end demand and supply plans across global product lines and inventory channels. Own the Sales & Operations Planning (S&OP) process and align supply plans with financial and business objectives. Collaborate with Finance, Sales, Marketing, and Engineering teams to support operational and product planning. Identify supply risks

Sr Software Engineer - Distributed Systems Engineer, EDA Infrastructure NVIDIA is hiring engineers to build and scale the infrastructure that supports our Electronic Design Automation (EDA) workloads. We are looking for engineers with strong programming skills, a deep understanding of distributed systems, experience operating large-scale production infrastructure, and excellent communication and planning abilities. You will help design reliable automation and platform services that manage large fleets of GPU-based and CPU-based compute systems used by engineering teams across NVIDIA. The ideal candidate is comfortable working across software, operating systems, cluster schedulers, networking, storage, and physical hardware. You should enjoy solving complex operational problems, eliminating repetitive work through automation, and building systems that remain reliable as infrastructure grows. If you are creative, pragmatic, and motivated to improve how critical engineering workloads are delivered, we would like to hear from you. What You Will Be Doing: Design and build platforms that automate the provisioning, configuration, operation, and lifecycle management of large-scale GPU and CPU compute infrastructure. Develop monitoring, health-management, and remediation systems that improve the reliability, availability, and utilization of EDA compute environments. Automate hardware deployment, operating-system configuration, firmware and software updates, cluster enrollment, and recovery workflows. Build reliable services and workflows that integrate with workload schedulers, infrastructure management systems, and observability platforms. Use hardware diagnostics, operating-system signals, scheduler data, and network and storage telemetry to identify

About the Role Lead a team of AI Infra (Systems Engineers) at Together based out of our office in Amsterdam, you and the SRE team are responsible for keeping all user-facing services and production systems running smoothly. You are a blend of a pragmatic operator and a software engineer that applies sound engineering principles, operational discipline, and mature automation to our operating environments and codebase. You specialize in systems (operating systems, storage subsystems, networking), while implementing best practices for availability, reliability and scalability, with varied interests in algorithms and distributed systems. Responsibilities Be on an on-call (PagerDuty) rotation to respond to incidents that impact availability Manage, develop and coach the SRE Team. Build and run our infrastructure with Ansible, Terraform, and Kubernetes to enable scaling to a massive number of concurrent users Build monitoring systems to ensure the highest quality service for our customers Design and implement operational processes (such as deployments and upgrades) Debug production issues across all services and levels of the stack Identify improvements for the product architecture from the reliability, performance and availability perspectives Plan the growth of Together AI’s infrastructure Requirements 7+ years of professional SRE or related experience Ideally 2 years as a Lead SRE Bachelor's degree in Computer Science or a related field or equivalent work experience Expert knowledge of Ansible (roles, playbooks), Terraform, and Kubernetes Proficiency in programming/scripting languages Direct experience in monitoring and observability practices Advanced knowledge of cloud services Ability to thrive in a collaborative environment involving different stakeholders and subject matter experts About Together AI Together AI, the AI Native Cloud, is purpose-built for AI engineers. AI application developers get high-performance inference that scales reliably, fine-tu

Role Overview As a Systems Research Engineer Intern specialized in GPU Programming, you will play a crucial role in developing and optimizing GPU-accelerated kernels and algorithms for ML/AI applications. Working closely with the modeling and algorithm team, you will co-design GPU kernels and model architecture to enhance the performance and efficiency of our AI systems. Collaborating with the hardware and software teams, you will contribute to the co-design of efficient GPU architectures and programming models, leveraging your expertise in GPU programming and parallel computing. Your research skills will be vital in staying up-to-date with the latest advancements in GPU programming techniques, ensuring that our AI infrastructure remains at the forefront of innovation. This internship is based on-site at our San Francisco HQ, running through the Winter term from January to April. Responsibilities Optimize and fine-tune GPU code to achieve better performance and scalability Collaborate with cross-functional teams to integrate GPU-accelerated solutions into existing software systems Stay up-to-date with the latest advancements in GPU programming techniques and technologies Requirements Strong background in GPU programming and parallel computing, such as CUDA and/or Triton. Knowledge of ML/AI applications and models Knowledge of performance profiling and optimization tools for GPU programming Excellent problem-solving and analytical skills About Together AI Together AI, the AI Native Cloud, is purpose-built for AI engineers. AI application developers get high-performance inference that scales reliably, fine-tuning and reinforcement learning for creating frontier-level specialized models, and pre-training at massive scale for fully custom intelligence, all around a marketplace of leading open models that teams can run, adapt, and own. Trusted by Cursor, Decagon, ElevenLabs, Salesforce, and Zoom, Together serves 400+ trillion tokens a month. Internship Program Details:&n

Role Overview As a Systems Research Engineer Intern specialized in GPU Programming, you will play a crucial role in developing and optimizing GPU-accelerated kernels and algorithms for ML/AI applications. Working closely with the modeling and algorithm team, you will co-design GPU kernels and model architecture to enhance the performance and efficiency of our AI systems. Collaborating with the hardware and software teams, you will contribute to the co-design of efficient GPU architectures and programming models, leveraging your expertise in GPU programming and parallel computing. Your research skills will be vital in staying up-to-date with the latest advancements in GPU programming techniques, ensuring that our AI infrastructure remains at the forefront of innovation. Responsibilities Optimize and fine-tune GPU code to achieve better performance and scalability Collaborate with cross-functional teams to integrate GPU-accelerated solutions into existing software systems Stay up-to-date with the latest advancements in GPU programming techniques and technologies Requirements Strong background in GPU programming and parallel computing, such as CUDA and/or Triton. Knowledge of ML/AI applications and models Knowledge of performance profiling and optimization tools for GPU programming Excellent problem-solving and analytical skills About Together AI Together AI, the AI Native Cloud, is purpose-built for AI engineers. AI application developers get high-performance inference that scales reliably, fine-tuning and reinforcement learning for creating frontier-level specialized models, and pre-training at massive scale for fully custom intelligence, all around a marketplace of leading open models that teams can run, adapt, and own. Trusted by Cursor, Decagon, ElevenLabs, Salesforce, and Zoom, Together serves 400+ trillion tokens a month. Internship Program Details: Our internship program runs 12 to 14 weeks, giving you the opportunity to work alongside industry-leading en

About the Role Together AI runs one of the largest GPU fleets in the world. The Infra Agent Systems team builds the software systems that power and automate that infrastructure. We develop production AI agents that diagnose hardware failures, investigate incidents, correlate signals across the fleet, and automate operational workflows. Alongside these agents, we build the platform they run on, including knowledge graphs, retrieval systems, orchestration frameworks, and developer tooling. You’ll work across two areas: Infrastructure Agent Systems — Build production AI agents that help operate our GPU fleet by diagnosing failures, investigating incidents, gathering evidence from live systems, and assisting with remediation. These agents are used every day by our infrastructure and datacenter teams through APIs, CLI, dashboards, and Slack. Core Agent Platform — Build the platform that powers these agents, including knowledge graphs, search and retrieval, orchestration, evaluation, and the tooling that enables agents to reason, act, and continuously improve. We’re working on something that hasn’t really been done before: building knowledge graphs and self-improving AI agents that understand, operate, and continuously improve large-scale AI infrastructure. This is an opportunity to work at the intersection of AI agents, distributed systems, infrastructure, and automation , solving challenging engineering problems with real production impact. There’s an enormous amount to build, learn, and shape as we define the future of autonomous infrastructure. Why this Role You’ll work on two hard problems at the same time: making AI agents trustworthy enough to operate production infrastructure, and building the knowledge, retrieval, and distributed systems that make those agents effective. You’ll have the opportunity to build foundational systems from the ground up, work on infrastructure at massive scale, and help define how self-improving AI agents operate real-world AI infrastru

About the Role Together AI runs one of the largest GPU fleets in the world. The Infra Agent Systems team builds the software systems that power and automate that infrastructure. We develop production AI agents that diagnose hardware failures, investigate incidents, correlate signals across the fleet, and automate operational workflows. Alongside these agents, we build the platform they run on, including knowledge graphs, retrieval systems, orchestration frameworks, and developer tooling. You’ll work across two areas: Infrastructure Agent Systems — Build production AI agents that help operate our GPU fleet by diagnosing failures, investigating incidents, gathering evidence from live systems, and assisting with remediation. These agents are used every day by our infrastructure and datacenter teams through APIs, CLI, dashboards, and Slack. Core Agent Platform — Build the platform that powers these agents, including knowledge graphs, search and retrieval, orchestration, evaluation, and the tooling that enables agents to reason, act, and continuously improve. We’re working on something that hasn’t really been done before: building knowledge graphs and self-improving AI agents that understand, operate, and continuously improve large-scale AI infrastructure. This is an opportunity to work at the intersection of AI agents, distributed systems, infrastructure, and automation , solving challenging engineering problems with real production impact. There’s an enormous amount to build, learn, and shape as we define the future of autonomous infrastructure. responsible for delivering the software but also for operating and supporting it in production. Why this Role You’ll work on two hard problems at the same time: making AI agents trustworthy enough to operate production infrastructure, and building the knowledge, retrieval, and distributed systems that make those agents effective. You’ll have the opportunity to build foundational systems from the ground up, work on infrastructur

About the Role Together AI runs one of the largest GPU fleets in the world. The Infra Agent Systems team builds the software systems that power and automate that infrastructure. We develop production AI agents that diagnose hardware failures, investigate incidents, correlate signals across the fleet, and automate operational workflows. Alongside these agents, we build the platform they run on, including knowledge graphs, retrieval systems, orchestration frameworks, and developer tooling. You’ll work across two areas: Infrastructure Agent Systems — Build production AI agents that help operate our GPU fleet by diagnosing failures, investigating incidents, gathering evidence from live systems, and assisting with remediation. These agents are used every day by our infrastructure and datacenter teams through APIs, CLI, dashboards, and Slack. Core Agent Platform — Build the platform that powers these agents, including knowledge graphs, search and retrieval, orchestration, evaluation, and the tooling that enables agents to reason, act, and continuously improve. We’re working on something that hasn’t really been done before: building knowledge graphs and self-improving AI agents that understand, operate, and continuously improve large-scale AI infrastructure. This is an opportunity to work at the intersection of AI agents, distributed systems, infrastructure, and automation , solving challenging engineering problems with real production impact. There’s an enormous amount to build, learn, and shape as we define the future of autonomous infrastructure. responsible for delivering the software but also for operating and supporting it in production. Why this Role You’ll work on two hard problems at the same time: making AI agents trustworthy enough to operate production infrastructure, and building the knowledge, retrieval, and distributed systems that make those agents effective. You’ll have the opportunity to build foundational systems from the ground up, work on infrastructur

About the Role Together AI runs one of the largest GPU fleets in the world. The Infra Agent Systems team builds the software systems that power and automate that infrastructure. We develop production AI agents that diagnose hardware failures, investigate incidents, correlate signals across the fleet, and automate operational workflows. Alongside these agents, we build the platform they run on, including knowledge graphs, retrieval systems, orchestration frameworks, and developer tooling. You’ll work across two areas: Infrastructure Agent Systems — Build production AI agents that help operate our GPU fleet by diagnosing failures, investigating incidents, gathering evidence from live systems, and assisting with remediation. These agents are used every day by our infrastructure and datacenter teams through APIs, CLI, dashboards, and Slack. Core Agent Platform — Build the platform that powers these agents, including knowledge graphs, search and retrieval, orchestration, evaluation, and the tooling that enables agents to reason, act, and continuously improve. We’re working on something that hasn’t really been done before: building knowledge graphs and self-improving AI agents that understand, operate, and continuously improve large-scale AI infrastructure. This is an opportunity to work at the intersection of AI agents, distributed systems, infrastructure, and automation , solving challenging engineering problems with real production impact. There’s an enormous amount to build, learn, and shape as we define the future of autonomous infrastructure. responsible for delivering the software but also for operating and supporting it in production. Why this Role You’ll work on two hard problems at the same time: making AI agents trustworthy enough to operate production infrastructure, and building the knowledge, retrieval, and distributed systems that make those agents effective. You’ll have the opportunity to build foundational systems from the ground up, work on infrastructur

About the Role As a Systems Research Engineer specialized in GPU Programming, you will play a crucial role in developing and optimizing GPU-accelerated kernels and algorithms for ML/AI applications. Working closely with the modeling and algorithm team, you will co-design GPU kernels and model architecture to enhance the performance and efficiency of our AI systems. Collaborating with the hardware and software teams, you will contribute to the co-design of efficient GPU architectures and programming models, leveraging your expertise in GPU programming and parallel computing. Your research skills will be vital in staying up-to-date with the latest advancements in GPU programming techniques, ensuring that our AI infrastructure remains at the forefront of innovation. Requirements Strong background in GPU programming and parallel computing, such as CUDA and/or Triton. Knowledge of ML/AI applications and models Knowledge of performance profiling and optimization tools for GPU programming Excellent problem-solving and analytical skills Bachelor's, Master's, or Ph.D. degree in Computer Science, Electrical Engineering, or equivalent practical experiences Responsibilities Optimize and fine-tune GPU code to achieve better performance and scalability Collaborate with cross-functional teams to integrate GPU-accelerated solutions into existing software systems Stay up-to-date with the latest advancements in GPU programming techniques and technologies About Together AI Together AI, the AI Native Cloud, is purpose-built for AI engineers. AI application developers get high-performance inference that scales reliably, fine-tuning and reinforcement learning for creating frontier-level specialized models, and pre-training at massive scale for fully custom intelligence, all around a marketplace of leading open models that teams can run, adapt, and own. Trusted by Cursor, Decagon, ElevenLabs, Salesforce, and Zoom, Together serves 400+ trillion tokens a month. Compensation We offer competi