Linux Infrastructure Engineer – Bare Metal, Storage, AI Factory Infrastructure

This is a fully remote position, open to applicants in Malaysia.

📋 Description

• Design, implement, manage, and troubleshoot extensive Linux-based infrastructure.

• Support both traditional enterprise workloads and contemporary AI/ML environments.

• Construct and oversee infrastructure from the hardware level, encompassing servers, networking, storage, GPU clusters, and AI-capable platforms.

• Deploy, provision, and maintain bare metal servers and BMaaS platforms throughout their entire lifecycle.

• Implement and oversee GPU-accelerated infrastructure, GPU clusters, and AI training/HPC environments.

• Monitor and enhance GPU performance while managing GPU resource allocation.

• Design and support enterprise storage solutions, Ceph clusters, high-performance AI storage, and parallel file systems.

• Create and troubleshoot high-performance data center networking and Layer 2/Layer 3 infrastructure.

• Ensure support for high-availability, clustering, disaster recovery, and mission-critical production environments.

• Resolve challenges related to operating systems, hardware, storage, networking, and AI infrastructure.

• Automate operational tasks leveraging Bash and Python.

• Develop operational documentation, runbooks, and infrastructure standards.

• Collaborate with the dedicated DevOps team while concentrating on infrastructure engineering instead of DevOps delivery pipelines.

⛳️ Requirements

• Expert-level proficiency in Linux administration; experience with Ubuntu is essential, while Red Hat and SUSE are preferred.

• In-depth knowledge of bare metal server deployment, architecture, provisioning, and lifecycle management.

• Familiarity with operating Bare Metal as a Service (BMaaS) platforms and extensive infrastructure environments.

• Strong comprehension of server hardware, including BIOS/UEFI, RAID controllers, firmware management, iLO/iDRAC/IPMI, NICs and SmartNICs, HBA cards, and hardware diagnostics.

• Experience in designing, implementing, and maintaining enterprise Linux infrastructure at scale.

• Proven experience in deploying and managing GPU-accelerated infrastructure for AI/ML workloads.

• Knowledge of NVIDIA GPU technologies, such as A100, H100, H200, B200, or similar platforms.

• Background with NVIDIA DGX and OEM GPU servers, including GPU provisioning, lifecycle management, monitoring, and performance enhancement.

• Understanding of AI Factory architecture and its infrastructure requirements.

• Experience in supporting GPU clusters, AI training environments, and HPC workloads.

• Familiarity with GPU resource allocation and scheduling, multi-GPU systems, GPU networking, and high-bandwidth, low-latency infrastructure design.

• Knowledge of CUDA, NCCL, GPUDirect Storage, NVIDIA Fabric Manager, and NVIDIA Base Command.

• Advanced expertise in Linux storage administration: LVM, XFS, EXT4, NFS, iSCSI, Fibre Channel SAN, and Multipath I/O.

• Significant hands-on experience with Ceph, including MON, OSD, MDS, RBD, CephFS, RGW, capacity planning, performance tuning, and failure recovery.

• Familiarity with high-performance AI storage platforms such as WEKA, VAST Data, Dell PowerScale, Pure Storage FlashBlade, and NetApp.

• Understanding of NVMe-over-Fabrics, RDMA, GPUDirect Storage, parallel file systems, and AI data pipelines.

• Strong networking expertise: bonding, VLANs, routing, MTU optimization, DNS, and DHCP.

• Experience with 100G/200G/400G Ethernet, RoCE, RDMA, and Spine-Leaf architectures.

• Familiarity with NVIDIA Spectrum-X, Mellanox/NVIDIA ConnectX adapters, or similar technologies.

• Solid understanding of Layer 2 and Layer 3 infrastructure design and troubleshooting.

• Experience with high availability, clustering, and disaster recovery.

• Strong troubleshooting abilities across Linux operating systems, hardware platforms, GPU infrastructure, networking, and enterprise storage.

• Proficiency in Bash and Python scripting for automation and operational efficiency.

• Experience in developing operational documentation, runbooks, and infrastructure standards.

• Familiarity with Kubernetes infrastructure, virtualization platforms, Ansible, NVIDIA Base Command Manager, Slurm/HPC schedulers, observability platforms, DCIM tools, IPAM solutions, and exposure to AWS/Azure or hybrid cloud is advantageous.

🏝️ Benefits

• Competitive salary and performance-based bonuses.

• Comprehensive health, dental, and vision insurance.

• Flexible working hours and remote work options.

• Opportunities for professional development and training.

• Collaborative and innovative work environment.