AI Systems Engineer

We are Lenovo. We do what we say. We own what we do. We WOW our customers.
Lenovo is a US$83 billion revenue global technology powerhouse, ranked #153 in the Fortune Global 500, and serving millions of customers every day in 180 markets. Focused on a bold vision to deliver Smarter Technology for All, Lenovo has built on its success as the world’s largest PC company with a full-stack portfolio of AI-enabled, AI-ready, and AI-optimized devices (PCs, workstations, smartphones, tablets), infrastructure (server, storage, edge, high performance computing and software defined infrastructure), software, solutions, and services. Lenovo’s continued investment in world-changing innovation is building a more equitable, trustworthy, and smarter future for everyone, everywhere. Lenovo is listed on the Hong Kong stock exchange under Lenovo Group Limited (HKSE: 992) (ADR: LNVGY).
This transformation together with Lenovo’s world-changing innovation is building a more inclusive, trustworthy, and smarter future for everyone, everywhere. To find out more visit www.lenovo.com (https://www.lenovo.com), and read about the latest news via our StoryHub (https://news.lenovo.com/).

Position Overview

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.

We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, color, sex, age, religion, sexual orientation, gender identity, national origin, status as a veteran, and basis of disability or any federal, state, or local protected class.