Advisory Engineer, AI Cluster Network Automation & Operations

Lenovo•Morrisville, NC

About The Position

Lenovo is seeking a senior, hands-on engineer to develop network automation and cluster operations capabilities for large-scale AI and HPC infrastructure. The role focuses on automating network configuration, bare-metal cluster deployment, infrastructure validation, and operational workflows across GPU-based compute environments. The engineer will contribute to ACTOR and the broader cluster management and validation framework, working across GPUs, NICs/DPUs, switches, management networks, infrastructure APIs, configuration management, monitoring, provisioning, and cluster validation. The role involves designing and building automation for AI cluster network deployment and configuration, including switch, NIC/DPU, and host-network configuration; cluster bring-up; topology discovery; connectivity validation; and configuration consistency checks. It also develops automation for bare-metal server and GPU-node discovery, provisioning, configuration, health checks, diagnostics, operational validation, and lifecycle management. The engineer supports configuration workflows for GPU and NIC/DPU drivers, firmware, operating systems, and infrastructure software, and integrates GPU health, network health, topology, inventory, telemetry, and infrastructure state into cluster-management workflows. Automation is developed primarily in Python and/or Go, with REST/API integrations, Ansible roles and playbooks, reusable components, and CI/CD and cluster-management integrations. The engineer designs error handling, rollback, telemetry, logging, and validation mechanisms for scalable infrastructure automation supporting hundreds to thousands of servers and network endpoints. The position is based in Morrisville, North Carolina. Lenovo describes itself as a global technology company with US$83 billion in revenue, serving customers in 180 markets and offering devices, infrastructure, software, solutions, and services.

Requirements

BS/MS in Computer Science, Computer Engineering, Electrical Engineering, or a related field.
8+ years of experience in networking, infrastructure automation, distributed systems, Linux systems, data-center engineering, AI infrastructure, or HPC environments.
Strong hands-on Linux experience.
Strong programming skills in Python, Go, C/C++, or similar languages.
Experience with configuration-management and automation technologies such as Ansible.
Strong understanding of Ethernet/IP networking and modern data-center network architectures.
Experience automating physical infrastructure using APIs, scripting, infrastructure-as-code, or configuration-management frameworks.
Experience supporting or automating bare-metal server deployment, provisioning, configuration, and validation workflows.
Understanding of server architecture, NICs, DPUs, switches, BMCs, operating systems, and infrastructure-management platforms.
Strong troubleshooting and root-cause-analysis skills.
Experience in large-scale data-center, AI infrastructure, HPC, hyperscale, cloud service provider (CSP), or NeoCloud environments.

Nice To Haves

Experience with InfiniBand and/or RoCE networking technologies.
Experience with data-center networking hardware, including NICs, DPUs, Ethernet switches, and/or InfiniBand switches, including technologies from NVIDIA, AMD, Broadcom, Cisco, Arista, Juniper, Dell, HPE, or similar vendors.
Experience with AI, GPU, HPC, or accelerated-computing clusters at scale.
Experience with NVIDIA ConnectX, BlueField, Spectrum, Spectrum-X, or comparable high-performance networking technologies.
Experience with Redfish, OpenBMC, BMC APIs, and bare-metal infrastructure automation.
Experience with NetBox or another DCIM/source-of-truth platform.
Experience with Kubernetes, Slurm, or comparable cluster-management systems.
Experience with Prometheus, Grafana, OpenTelemetry, or similar infrastructure telemetry systems.
Familiarity with GPUDirect RDMA, NCCL, distributed AI communication frameworks, or large-scale AI training/inference environments.
Experience building infrastructure automation for hundreds or thousands of servers, GPUs, and network endpoints.
Experience with CSP, hyperscale, NeoCloud, AI infrastructure, HPC, or large-scale data-center environments.

Responsibilities

Design and develop automation for AI cluster network deployment and configuration.
Automate switch, NIC/DPU, and host-network configuration.
Develop workflows for cluster bring-up, deployment, validation, and operational readiness.
Automate network topology discovery, connectivity validation, and configuration consistency checks.
Build reusable configuration templates and infrastructure automation frameworks.
Integrate network automation with cluster provisioning, health monitoring, and lifecycle-management workflows.
Automate bare-metal server and GPU-node discovery, provisioning, configuration, health checks, operational validation, and lifecycle management.
Develop and maintain bare-metal infrastructure deployment and validation workflows for large-scale AI/HPC clusters.
Support configuration workflows for GPU drivers, NIC/DPU drivers, firmware, operating systems, and infrastructure software.
Develop automated diagnostics and root-cause-analysis workflows for cluster hardware, networking, and software issues.
Integrate GPU health, network health, topology, inventory, telemetry, and infrastructure state into cluster-management workflows.
Develop automation for cluster readiness, operational qualification, and ongoing validation at scale.
Develop automation primarily using Python and/or Go.
Build REST/API-driven integrations with network, compute, storage, and infrastructure-management platforms.
Develop Ansible roles/playbooks and reusable automation components where appropriate.
Integrate automation into CI/CD and cluster-management frameworks.
Design error handling, rollback, telemetry, logging, and validation mechanisms for infrastructure automation.
Develop scalable automation supporting hundreds to thousands of servers and network endpoints.