AI Systems Engineer

Lenovo's Infrastructure Solutions Group (ISG) is seeking an experienced AI Systems Engineer to help design, deploy, automate, validate, and scale next-generation AI infrastructure platforms. This role sits at the intersection of software engineering, infrastructure automation, high-performance networking, and AI cluster operations. The ideal candidate will have hands-on experience building and supporting large-scale GPU-based environments used for AI training and inference, with strong expertise in Linux systems, distributed infrastructure, cluster validation, observability, and automation.

You will work closely with cross-functional engineering teams to develop scalable software solutions that automate AI cluster deployment, validation, monitoring, and operational readiness across GPU, networking, storage, and compute platforms.

Key Responsibilities

• Design and develop software and automation frameworks for AI cluster deployment, provisioning, configuration management, and lifecycle management.
• Build and maintain bare-metal infrastructure workflows, including hardware discovery, inventory management, cluster bring-up, validation, and operational readiness.
• Develop automation solutions for GPUs, CPUs, NICs/DPUs, storage platforms, networking infrastructure, and data center systems.
• Automate deployment, topology discovery, validation, and compliance of Ethernet, RoCE, and InfiniBand fabrics.
• Create cluster qualification, benchmarking, acceptance testing, and validation frameworks for large-scale AI infrastructure.
• Integrate telemetry, monitoring, observability, and health validation into infrastructure management workflows.
• Develop production-quality software using Python, Go, APIs, and infrastructure automation technologies.
• Troubleshoot and resolve hardware, firmware, software, networking, and performance issues across AI environments.
• Collaborate with platform, hardware, software, and AI engineering teams to improve deployment efficiency, scalability, reliability, and performance.

Basic Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, or a related technical discipline, or equivalent experience.
• 5+ years of experience in software engineering, infrastructure automation, distributed systems, Linux systems, networking, data center infrastructure, or related technical fields.
• Strong programming and software development experience in Python, Go, C/C++, and/or Rust.
• Experience developing and consuming APIs and working with automation frameworks such as Ansible.
• Strong understanding of Linux operating systems, distributed systems, networking, server architecture, and modern data center infrastructure.
• Experience with GPUs, high-performance compute environments, networking technologies, and infrastructure management systems.
• Proven ability to troubleshoot complex infrastructure, networking, software, and system-level issues.

Preferred Qualifications

• Experience supporting AI/HPC infrastructure, GPU clusters, and distributed computing environments.
• Experience with NVIDIA CUDA, NCCL, GPUDirect RDMA, AMD ROCm, or related accelerator ecosystems.
• Hands-on experience with InfiniBand, RoCE, RDMA, and high-performance networking technologies.
• Experience with Redfish, BMC APIs, NetBox, Kubernetes, Slurm, OpenShift, Kubeflow, KubeRay, or similar infrastructure management platforms.
• Experience with Prometheus, Grafana, OpenTelemetry, and full-stack observability solutions.
• Experience supporting AI training, fine-tuning, inference, RAG, agentic AI, or large-scale machine learning platforms.
• Experience in hyperscale cloud, CSP, NeoCloud, enterprise AI, or HPC environments.
• Experience with performance optimization, system integration, benchmarking, and infrastructure scalability initiatives.