AI Systems Architect
UltaHost
WorldwideFully remoteFull TimeSeniorInformation Technology
Posted 2 hours ago2h agoApply link checked 1 hour ago
Why we think you can apply
- Hiring model
- Open worldwide · the employer states no country restriction
- Work from
- Anywhere, the UAE included
Posted 2 hours ago · apply link checked 1 hour ago
About the role
Responsibilities
- Design and operate infrastructure for LLM and AI workloads on GPU-enabled servers
- Design Proxmox, KVM and container virtualization strategies for AI workloads
- Deploy, benchmark and optimize self-hosted and third-party LLMs
- Build production AI applications, RAG systems, agents and APIs
- Integrate AI systems with UltaHost platforms, portals and internal tools
- Automate infrastructure provisioning and deployment workflows
- Apply least-privilege, isolation and governance controls to AI systems
- Identify business workflows where AI or deterministic automation reduces manual work
Requirements
- Strong Linux administration and troubleshooting
- Hands-on KVM or Proxmox VE virtualization experience
- Strong Docker and containerization knowledge
- Practical understanding of GPU, VRAM, quantization and inference performance
- Experience building and deploying LLM or RAG applications
- Python or TypeScript/Node.js backend development
- Networking fundamentals: TCP/IP, DNS, TLS, firewalls, reverse proxies
- At least 5 years in infrastructure, platform, DevOps or backend systems
- At least 2-3 years building or operating AI-powered systems
- Professional working proficiency in English
Preferred Qualifications
- NVIDIA GPU and CUDA ecosystem experience
- vLLM, Ollama, LiteLLM or Triton experience
- Vector databases such as Qdrant or pgvector
- Terraform, Ansible and Kubernetes
- Observability tooling such as Prometheus, Grafana or OpenTelemetry
About the Company
- UltaHost is a global web hosting and cloud infrastructure company founded in 2018.
- It provides VPS, dedicated, shared hosting, domains and cloud services worldwide.
What we look for
- Strong Linux administration and troubleshooting
- Hands-on KVM or Proxmox VE virtualization experience
- Strong Docker and containerization knowledge
- Practical understanding of GPU, VRAM, quantization and inference performance
- Experience building and deploying LLM or RAG applications
- Python or TypeScript/Node.js backend development
- Networking fundamentals: TCP/IP, DNS, TLS, firewalls, reverse proxies
- At least 5 years in infrastructure, platform, DevOps or backend systems
- At least 2-3 years building or operating AI-powered systems
- Professional working proficiency in English
- NVIDIA GPU and CUDA ecosystem experience
- vLLM, Ollama, LiteLLM or Triton experience
PythonTypeScriptNode.jsDockerKubernetesLinuxPostgreSQLTerraformLLMAnsibleRAGLangChainOllamavLLMProxmox VE
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UltaHost
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