Senior Platform Engineer - GPUaaS, Data Infrastructure and Agentic AI

RoleOverview

We are looking for a senior, hands\-on platform engineer to design and build cloud\-likeGPU and data platforms in on\-prem and hybridenvironments, with a strong focus on performance,scale, and autonomy.

KeyResponsibilities

GPU\-as\-a\-Service/ GPU Virtualization

• Design and build GPUaaS platforms for AI/ML and data workloads
• Implement GPU orchestration and scheduling using Kubernetes
• Enable GPU sharing, isolation, and quota management using technologies such as MIG, vGPU, or device plugins
• Optimize GPU utilization, performance, and cost efficiency
• Integrate GPU platforms with multi\-tenant access control, billing, and observability

Required Skills & Experience

• 8+ years of experience in infrastructure, platform, or systems engineering
• Proven experience building GPU virtualization or GPUaaS platforms
• Strong understanding of Linux internals, K8 networking, and storage systems like CEPH
• Experience with Kubernetes and containerized workloads
• Proficiency in automation and scripting (Python, Bash, Go, or similar)
• Experience building automation or autonomous systems that interact with real infrastructure

Preferred Skills

• Experience with NVIDIA GPU technologies (MIG, vGPU, CUDA, DCGM)
• Experience with Kubernetes GPU device plugins and scheduling
• Experience with distributed storage systems (Ceph, object storage, etc.)
• Experience building multi\-tenant platforms with strong isolation and security using CNIs like Cilium, Calico