We are seeking an experienced Data Center Virtualization Engineer with deep expertise in GPU and hardware accelerator technologies. In this role, you'll be instrumental in building and managing a cloud-based, ARM and x86-compatible virtual environment with GPU sharing capabilities. Your work will support fully virtualized development and testing environments for advanced hardware emulation and cross-architecture compatibility.

Key Responsibilities

• Configure, optimize, and manage bare metal AWS cloud instances (including Graviton and G4DN) to support ARM and x86 emulation with GPU acceleration.

• Develop and maintain multi-architecture, cross-compiled containers using Docker Buildx, GCC toolchains, QEMU, and related tools to enable scalable GPGPU emulation.

• Collaborate with software and hardware engineering teams to ensure drivers, applications, and dependencies are fully optimized for hybrid ARM/x86 environments.

• Implement and manage container orchestration platforms (e.g., K3s, Kubernetes) for OCI-compliant containers, with a focus on efficient GPU utilization and cross-platform performance.

• Lead ARM and x86 cross-compilation efforts, ensuring high performance, security, and scalability across the virtualized dev/test lifecycle.

• Integrate SDWAN solutions into the emulated environment in collaboration with networking teams to meet high-bandwidth, low-latency requirements.

• Harden container environments for security and compliance, particularly around GPU access, data integrity, and architecture-specific vulnerabilities.

Qualifications

• 5+ years of experience in virtualization, containerization, and cross-architecture systems.

• Deep knowledge of AWS services including GPU-enabled and bare metal instances (e.g., AWS Graviton, G4DN).

• Strong expertise in multi-architecture container development using GCC/LLVM toolchains and Docker Buildx.

• Hands-on experience with NVIDIA Enterprise GPU drivers, CUDA, and GPU management in containerized environments.

• Proficient in container orchestration platforms such as Kubernetes or K3s.

• Familiar with SDWAN implementation, emulation frameworks (e.g., ARM-on-x86), and multi-instance networking configurations.

• Advanced Linux knowledge including kernel compilation, driver integration, and low-level hardware interaction.

Preferred Qualifications

• Experience in high-performance computing (HPC) and managing GPU-accelerated workloads.

• Strong understanding of security best practices in virtualized and containerized environments.

• Familiarity with hybrid or multi-cloud infrastructure strategies and deployments.