AI System Engineer

About the role

This role supports pre-sales activities, technical demonstrations, and customer engagement across two specialization tracks: AI/Server/HCI infrastructure or Physical AI robotics. You will work with cutting-edge technologies including GPU servers, containerized workloads, Kubernetes, HCI platforms, and AI-powered humanoid robots, depending on your track assignment.

Key responsibilities

• Support pre-sales activities and technical demos for GPU servers, HCI platforms (e.g. Nutanix, VMware, Proxmox), and AI infrastructure
• Help deploy and manage containerized workloads on Kubernetes (K8s) for AI infrastructure and related use cases
• Research new products (GPU, servers, storage) and summarize findings into clear, accessible documentation for the sales team and customers
• Help prepare technical proposal documents, including Bill of Materials (BOM) and spec sheets
• Test, set up, and integrate AI-powered humanoid robots with systems and AI models as required by the project
• Prepare and run Physical AI demos for customers
• Research new robotics products and summarize findings into clear, accessible documentation for the sales team and customers
• Prepare and run product demos and Proof of Concept (POC) sessions for customers
• Collaborate with the sales team to provide technical input and answer customer questions
• Provide basic customer support and track issues/cases through a ticketing or case-tracking system

About you

• Bachelor's degree in Computer Engineering, Electrical Engineering, Computer Science, Mechatronics, or a related field
• Interest in or foundational knowledge of at least one of: AI, Server/Datacenter Infrastructure, Virtualization/HCI, Kubernetes/DevOps, or Robotics
• Fast learner with a strong drive for self-directed research into new technologies
• English proficiency sufficient to read technical documentation
• Open to fresh graduates; prior work experience is not required
• Experience with Linux or basic scripting (Python / Bash)
• Foundational knowledge of networking or virtualization (VMware, Nutanix, Proxmox, etc.)
• Foundational knowledge of Kubernetes (K8s), microservices architecture, or DevOps practices (e.g. CI/CD)
• Coursework or personal projects involving robotics or ROS
• Experience deploying AI models on physical devices (embedded/edge)