AI Infrastructure Systems Engineer

About the role

AI Infrastructure Systems Engineer Build the infrastructure powering the next generation of AI. At Together AI, you’ll build and operate one of the world’s largest GPU fleets used for frontier model training and inference. This isn’t a traditional infrastructure role—we’re looking for engineers who love building systems, automating everything, and solving problems at massive scale. You’ll Thrive Here If You: - Love building systems that replace repetitive operational work. - Think of infrastructure as a software engineering problem. - Enjoy solving hard problems with no existing playbook. - Care deeply about performance, reliability, and scale. - Want to build technology that powers frontier AI models. Our mission is simple: build AI infrastructure that largely runs itself—where intelligent systems deploy, monitor, diagnose, optimize, and heal GPU fleets at massive scale. Every system you build will directly improve the speed, efficiency, and reliability of one of the world’s most advanced AI compute platforms. If you enjoy writing software more than clicking dashboards, obsess over eliminating manual work, and want to build infrastructure that manages tens of thousands of GPUs autonomously, we’d love to talk. Responsibilities - Design and build fleet automation systems that provision, validate, deploy, upgrade, repair, and retire GPU clusters with minimal human intervention. - Build AI Infrastructure Agents that automate deployment, root-cause failures, incident triage, and autonomous remediation. - Develop Fleet Intelligence platforms that continuously monitor hardware health, firmware, networking, storage, thermals, and workload performance to predict failures before they impact customers. - Build software that maximizes GPU availability, utilization, performance, and reliability across thousands of accelerators. - Create automated validation systems for GPUs, InfiniBand/RoCE fabrics, NVLink/NVSwitch, storage, and distributed AI workloads. - Build internal platforms and developer tools that allow infrastructure to be managed through software—not manual operations. - Continuously improve deployment velocity, reliability, and operational efficiency through automation. - Partner closely with hardware, networking, platform, and AI teams to push the limits of AI infrastructure. Requirements - 3+ years building distributed systems, infrastructure platforms, or large-scale backend software. - Strong software engineering skills in Python, Go, or Rust. - Experience building platforms, automation systems, or developer infrastructure. - Experience with Linux, Kubernetes, Terraform, Ansible, or similar infrastructure technologies. - Strong systems thinking with the ability to understand problems across hardware and software. - A passion for solving complex infrastructure challenges through software. - An automation-first mindset—if a task is repeated, your instinct is to build a system to eliminate it. Bonus Experience - GPU infrastructure, CUDA, NCCL, NVLink/NVSwitch - InfiniBand or RoCE networking - Bare-metal provisioning and lifecycle management - Large-scale AI training or inference clusters - Hardware health monitoring and predictive failure detection - Distributed storage systems - AI agents and autonomous infrastructure operations About Together AI Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers and engineers in our journey in building the next generation AI infrastructure. Compensation We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $190,000 - $270,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge. Equal Opportunity Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more. San Francisco

Key responsibilities

• check_circleCollaborate with the team on day-to-day project tasks
• check_circleLearn tools and processes used by the organization
• check_circleDocument work and participate in team meetings
• check_circleSupport quality checks and continuous improvement

Requirements

• check_circleLove building systems that replace repetitive operational work.
• check_circleThink of infrastructure as a software engineering problem.
• check_circleEnjoy solving hard problems with no existing playbook.
• check_circleCare deeply about performance, reliability, and scale.
• check_circleWant to build technology that powers frontier AI models.
• check_circleDesign and build fleet automation systems that provision, validate, deploy, upgrade, repair, and retire GPU clusters with minimal human intervention.
• check_circleBuild AI Infrastructure Agents that automate deployment, root-cause failures, incident triage, and autonomous remediation.
• check_circleDevelop Fleet Intelligence platforms that continuously monitor hardware health, firmware, networking, storage, thermals, and workload performance to predict failures before they impact customers.
• check_circleBuild software that maximizes GPU availability, utilization, performance, and reliability across thousands of accelerators.
• check_circleCreate automated validation systems for GPUs, InfiniBand/RoCE fabrics, NVLink/NVSwitch, storage, and distributed AI workloads.
• check_circleBuild internal platforms and developer tools that allow infrastructure to be managed through software—not manual operations.
• check_circleContinuously improve deployment velocity, reliability, and operational efficiency through automation.

Skills & keywords

Benefits & perks

• check_circleMentorship
• check_circleCertificate of completion
• check_circleFlexible work arrangement where applicable