remote
Senior Manager, AI Cluster Deployment
Software Engineer
Lead the design, deployment, and operational readiness of large‑scale GPU clusters for AI training and inference, leveraging automation, Kubernetes, and cloud/hybrid infrastructure.
About the role
Key Responsibilities
- Architect and execute end‑to‑end deployment of production‑grade GPU clusters across cloud, hybrid, and on‑premises data centers.
- Drive automation strategy using Ansible, Terraform, and custom Python tooling to streamline provisioning, configuration, and scaling.
- Collaborate with networking and storage teams to ensure high‑throughput, low‑latency connectivity and optimal data pipelines for AI workloads.
- Lead a cross‑functional team of engineers, providing technical guidance, mentorship, and performance management.
- Establish operational readiness processes, including monitoring, alerting, capacity planning, and incident response for AI infrastructure.
Requirements
- 10+ years of experience in data‑center or cloud infrastructure, with at least 5 years focused on GPU‑based AI clusters.
- Strong expertise in Linux systems, networking (TCP/IP, RDMA), and high‑performance storage solutions.
- Proven hands‑on experience with Kubernetes orchestration, Ansible, Terraform, and Python scripting for large‑scale automation.
- Demonstrated ability to lead technical teams, manage complex projects, and deliver solutions on schedule.
- Experience with major cloud platforms (AWS, Azure, GCP) and hybrid deployment models.
Skills
pythonkubernetesansibleterraformlinux