Senior System Architect

1 week ago

Singapore CLOUDENGINE DIGITAL PTE. LTD. Full time

**Position Overview**

**Key Responsibilities**
- System Architecture & Design
- Lead the end-to-end design of enterprise-grade server systems, including compute, storage, and networking components.
- Define architectural standards, guidelines, and best practices for large-scale deployments.
- Drive infrastructure scalability, performance, and reliability improvements.
- GPU & AI Workloads
- Architect and optimize GPU server platforms for AI/ML training and inference.
- Evaluate emerging hardware accelerators (GPU, DPU, FPGA) for integration into server environments.
- Collaborate with AI/ML teams to align system designs with model training and deployment requirements.
- Networking & Storage
- Design and oversee high-performance networking architectures (InfiniBand, RoCE, Ethernet) for HPC and AI clusters.
- Architect storage solutions (SAN, NAS, object storage, NVMe, distributed storage) to support data-intensive workloads.
- Ensure optimized data flow between compute, storage, and network layers.
- Technical Leadership
- Mentor junior engineers and guide cross-functional teams in system integration projects.
- Conduct technology evaluations, PoCs, and vendor assessments.
- Contribute to long-term IT strategy and infrastructure roadmap.

**Qualifications**

Education & Experience
- Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or related field.
- 8+ years of experience in system architecture, server design, or data center engineering.

Technical Skills
- Strong expertise in server hardware (CPU, GPU, memory, storage subsystems).
- Proven experience with GPU computing (e.g., NVIDIA CUDA, GPU clusters, HPC).
- Knowledge of network architecture (Ethernet, InfiniBand, RDMA, SDN) and storage technologies (RAID, SAN/NAS, NVMe, distributed storage).
- Familiarity with cloud platforms, virtualization, and container technologies (VMware, KVM, Docker, Kubernetes).
- Experience in system performance tuning, benchmarking, and capacity planning.

Soft Skills
- Strong analytical and problem-solving skills.
- Excellent communication and leadership abilities.
- Ability to work collaboratively across multiple teams and global environments.

**Preferred Qualifications**
- Hands-on experience with AI/ML infrastructure, large-scale GPU clusters, or HPC systems.
- Knowledge of emerging technologies such as DPUs, SmartNICs, and liquid cooling.
- Familiarity with DevOps practices and Infrastructure-as-Code (e.g., Ansible, Terraform).
- Industry certifications (e.g., NVIDIA, Red Hat, VMware, Cisco) are a plus.

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