{"schemaVersion":"jobsearcher.job.v1","id":"bb383894a0fad4fc42faedf3","url":"https://jobsearcher.com/jobs/bb383894a0fad4fc42faedf3","canonicalUrl":"https://jobsearcher.com/jobs/bb383894a0fad4fc42faedf3","title":"Cloud / DevOps Engineer, AI Compute Infrastructure","description":"Position Summary\nRichtech Robotics is looking for a Cloud / DevOps Engineer to support our AI compute infrastructure services. This role will help deploy, manage, and support cloud-based GPU environments for customers building AI models, robotics applications, simulation workflows, and Physical AI systems. The ideal candidate has strong Linux, networking, cloud infrastructure, and DevOps experience, with a willingness to learn GPU computing, CUDA environments, and AI workload deployment.\nResponsibilities\nDeploy and manage cloud-based GPU compute environments for customer workloads.\nConfigure virtual networks, VPNs, firewalls, security groups, SSH access, storage, and user permissions.\nBuild and maintain Linux-based environments for AI development, including Docker containers, CUDA drivers, Python environments, and Jupyter notebooks.\nWork with AI engineers to deploy required runtime environments for model training, fine-tuning, simulation, and inference.\nMonitor GPU usage, system performance, uptime, storage, and network connectivity.\nTroubleshoot customer issues related to access, environment setup, networking, storage, and compute availability.\nCreate reusable deployment scripts, images, templates, and technical documentation.\nCoordinate with cloud infrastructure partners and internal teams to resolve technical issues.\nRequired Qualifications\n2+ years of experience in cloud infrastructure, DevOps, systems administration, or network engineering.\nStrong Linux administration skills.\nSolid understanding of networking, including TCP/IP, VPN, DNS, firewalls, routing, security groups, and private networks.\nExperience with Docker and containerized environments.\nExperience with at least one major cloud platform or private cloud environment.\nFamiliarity with monitoring, logging, automation, and scripting.\nAbility to troubleshoot infrastructure issues independently.\nStrong communication skills and willingness to support customer-facing technical requests.\nInterest in learning GPU computing, CUDA environments, and AI infrastructure.\nPreferred Qualifications\nExperience deploying NVIDIA GPU drivers, CUDA, cuDNN, or NVIDIA Container Toolkit.\nFamiliarity with PyTorch, TensorFlow, Hugging Face, Jupyter, or vLLM.\nExperience with Slurm or distributed compute environments.\nExperience with Prometheus, Grafana, ELK, or similar monitoring tools.\nPrior experience supporting AI/ML, data science, robotics, or simulation workload\nPay: $80,000.00 - $120,000.00 per year\nBenefits:\nDental insurance\nHealth insurance\nPaid time off\nVision insurance\nWork Location: In person","company":"Richtech Robotics","rawCompany":"richtech robotics","city":"Las Vegas","state":"NV","isRemote":false,"isActive":false,"createdAt":"2026-08-04T16:44:53.637Z","occupations":[{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"},{"code":"15-1244.00","title":"Network and Computer Systems Administrators","slug":"network-and-computer-systems-administrators"},{"code":"15-1231.00","title":"Computer Network Support Specialists","slug":"computer-network-support-specialists"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"518210","title":"Computing Infrastructure Providers, Data Processing, Web Hosting, and Related Services","slug":"computing-infrastructure-providers-data-processing-web-hosting-and-related-services"},{"code":"541513","title":"Computer Facilities Management Services","slug":"computer-facilities-management-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Cloud / DevOps Engineer, AI Compute Infrastructure","description":"Position Summary\nRichtech Robotics is looking for a Cloud / DevOps Engineer to support our AI compute infrastructure services. This role will help deploy, manage, and support cloud-based GPU environments for customers building AI models, robotics applications, simulation workflows, and Physical AI systems. The ideal candidate has strong Linux, networking, cloud infrastructure, and DevOps experience, with a willingness to learn GPU computing, CUDA environments, and AI workload deployment.\nResponsibilities\nDeploy and manage cloud-based GPU compute environments for customer workloads.\nConfigure virtual networks, VPNs, firewalls, security groups, SSH access, storage, and user permissions.\nBuild and maintain Linux-based environments for AI development, including Docker containers, CUDA drivers, Python environments, and Jupyter notebooks.\nWork with AI engineers to deploy required runtime environments for model training, fine-tuning, simulation, and inference.\nMonitor GPU usage, system performance, uptime, storage, and network connectivity.\nTroubleshoot customer issues related to access, environment setup, networking, storage, and compute availability.\nCreate reusable deployment scripts, images, templates, and technical documentation.\nCoordinate with cloud infrastructure partners and internal teams to resolve technical issues.\nRequired Qualifications\n2+ years of experience in cloud infrastructure, DevOps, systems administration, or network engineering.\nStrong Linux administration skills.\nSolid understanding of networking, including TCP/IP, VPN, DNS, firewalls, routing, security groups, and private networks.\nExperience with Docker and containerized environments.\nExperience with at least one major cloud platform or private cloud environment.\nFamiliarity with monitoring, logging, automation, and scripting.\nAbility to troubleshoot infrastructure issues independently.\nStrong communication skills and willingness to support customer-facing technical requests.\nInterest in learning GPU computing, CUDA environments, and AI infrastructure.\nPreferred Qualifications\nExperience deploying NVIDIA GPU drivers, CUDA, cuDNN, or NVIDIA Container Toolkit.\nFamiliarity with PyTorch, TensorFlow, Hugging Face, Jupyter, or vLLM.\nExperience with Slurm or distributed compute environments.\nExperience with Prometheus, Grafana, ELK, or similar monitoring tools.\nPrior experience supporting AI/ML, data science, robotics, or simulation workload\nPay: $80,000.00 - $120,000.00 per year\nBenefits:\nDental insurance\nHealth insurance\nPaid time off\nVision insurance\nWork Location: In person","datePosted":"2026-08-04T16:44:53.637Z","dateModified":"2026-08-04T16:44:53.637Z","hiringOrganization":{"@type":"Organization","name":"Richtech Robotics","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Las Vegas","addressRegion":"NV","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"bb383894a0fad4fc42faedf3"},"url":"https://jobsearcher.com/jobs/bb383894a0fad4fc42faedf3"}}