AI/HPC Systems Engineer

Saige Partners•San Jose, CA

11d

About The Position

We are seeking an AI/HPC Systems Engineer to build, deploy, and operate the compute infrastructure supporting high-performance computing and AI development workloads. This role will focus on deploying, automating, and maintaining GPU-enabled environments across on-premises and cloud platforms while delivering reliable, scalable, and cost-effective computing resources for engineering and R&D teams. The ideal candidate brings hands-on experience with Linux infrastructure, GPU/HPC environments, cloud platforms, automation, and modern AI/ML infrastructure.

Requirements

Bachelor's degree in Computer Science, Engineering, or a related technical field.
3+ years of hands-on experience in IT infrastructure, cloud engineering, platform engineering, HPC, or a related field.
Hands-on experience with Linux-based infrastructure and public cloud platforms such as AWS, Azure, or GCP.
Experience deploying, configuring, or operating GPU and/or HPC environments.
Experience with workload scheduling or orchestration technologies such as Kubernetes, Slurm, or similar platforms.
Experience with infrastructure automation, monitoring, troubleshooting, and performance optimization.
Strong understanding of compute, storage, networking, virtualization, and container technologies.
Strong problem-solving, collaboration, and communication skills.
Ability to work effectively across engineering, R&D, and IT teams.

Nice To Haves

Experience supporting AI/ML infrastructure or workloads is a plus.

Responsibilities

Build, configure, and operate GPU and HPC clusters across compute, storage, and networking environments.
Support capacity planning, performance tuning, and infrastructure optimization for AI training, inference, and compute-intensive workloads.
Monitor system performance, availability, and resource utilization to ensure reliable operations.
Deploy and maintain computing environments across on-premises infrastructure and public cloud platforms.
Support infrastructure modernization, expansion, and scaling initiatives for HPC and AI workloads.
Help evaluate and implement solutions that improve scalability, reliability, and cost efficiency.
Implement infrastructure-as-code and automated provisioning solutions.
Develop and maintain monitoring, logging, alerting, and observability capabilities.
Automate routine infrastructure tasks and identify opportunities to improve resource utilization and operational efficiency.
Deploy, integrate, and support LLM APIs, coding assistants, and AI/agent platforms used by engineering teams.
Assist with the infrastructure requirements and operational support of AI/ML workloads.
Collaborate with engineering teams to ensure AI platforms are reliable, accessible, and scalable.
Troubleshoot and resolve infrastructure, networking, compute, storage, and platform issues.
Support day-to-day IT and infrastructure operations across engineering environments.
Develop and maintain technical documentation, standards, procedures, and operational runbooks.
Collaborate with engineering, IT, and other stakeholders to deliver reliable infrastructure solutions.