High Performance Compute HPC Lead / HPC Architect (Linux, GPU, Cloud HPC)

HPC Lead / HPC Architect (Linux, GPU, Cloud HPC) - 8+ Years Experience

Role Overview

We are looking for an experienced HPC Lead / HPC Architect to design, implement, and manage large-scale High Performance Computing (HPC) environments. This role will drive architecture, performance optimization, and transformation initiatives across compute (CPU/GPU), storage, and high-speed networking, supporting AI/ML, research, and enterprise workloads.

Key Responsibilities

• Lead architecture, design, and deployment of HPC clusters (CPU & GPU computing environments)
• Own the end-to-end HPC lifecycle: design, build, deployment, operations, and optimization
• Define and manage job scheduling systems (Slurm, PBS, LSF) and workload orchestration
• Drive performance tuning, benchmarking, and optimization for compute-intensive workloads (AI/ML, simulation, analytics)
• Architect and manage high-performance storage systems (Lustre, GPFS/IBM Spectrum Scale, BeeGFS)
• Design and implement low-latency, high-throughput networking (InfiniBand, RDMA, high-speed Ethernet)
• Lead hybrid and cloud HPC integration (AWS, Azure, GCP HPC solutions)
• Build and maintain automation frameworks (Ansible, Terraform, Infrastructure as Code, scripting)
• Implement monitoring, observability, logging, and capacity planning (Prometheus, Grafana, ELK, AIOps tools)
• Ensure security, compliance, identity and access management (IAM, LDAP/AD)
• Collaborate with research teams, data scientists, application owners, and business stakeholders
• Mentor and lead HPC engineers, system administrators, and infrastructure teams
• Drive innovation in GPU computing, AI/ML infrastructure, and advanced automation

Required Skills & Experience

• 8+ years of experience in HPC, Infrastructure Engineering, or Linux System Engineering
• Proven expertise in:HPC cluster architecture, deployment, and operationsLinux/Unix systems administration at scale (RHEL, CentOS, Ubuntu)CPU and GPU computing environments (NVIDIA GPU, CUDA preferred)
• Strong hands-on experience with:Job schedulers (Slurm, PBS, LSF)High-performance distributed storage (Lustre, GPFS, BeeGFS)Networking (TCP/IP, DNS, InfiniBand, RDMA, low-latency fabrics)
• Experience in automation and scripting (Python, Bash/Shell, Ansible, Terraform)
• Knowledge of cloud HPC architectures (AWS ParallelCluster, Azure CycleCloud, GCP HPC)

Preferred / Nice-to-Have Skills

• Experience with AI/ML infrastructure, deep learning workloads, or research computing
• Familiarity with containerization and orchestration (Docker, Kubernetes for HPC workloads)
• Exposure to observability platforms, AIOps, and predictive monitoring
• Experience in large-scale enterprise, research institutes, or university HPC environments
• Knowledge of DevOps / Platform Engineering practices

Leadership & Profile

• Strong stakeholder management and cross-functional collaboration skills
• Ability to translate business or research requirements into scalable HPC architecture
• Proven experience in team leadership, mentoring, and technical decision-making
• Strategic mindset with hands-on technical depth in HPC systems and infrastructure