Essential Skills

- HPC & AI Infrastructure:
- Expert-level knowledge of NVIDIA Base Command Manager (BCM) or Metal-as-a-Service (MaaS) provisioning tools.
- Deep understanding of Slurm configuration (cgroups, plugin development, accounting).
- Proficiency with NVIDIA DGX/HGX hardware architecture and the associated software stack (Drivers, CUDA, DCGM).

- Linux & Automation (DevOps for Hardware):

- Mastery of Red Hat Enterprise Linux (RHEL) / Ubuntu internals (Systemd, Kernel Tuning, Hugepages).
- Advanced proficiency in Ansible (writing custom modules/roles) and Python (automating admin tasks).
- Experience with Git workflows (Branching, PRs, CI/CD).

- Containerisation:

- Hands-on experience with Docker, Singularity/Apptainer, and Kubernetes (specifically NVIDIA GPU Operator and NVIDIA Network Operator).

Desirable Experience

- Network Awareness: Ability to troubleshoot basic InfiniBand/RoCEv2 issues (ibstat, perf query)



to distinguish between a "Node Issue" and a "Network Issue."
- Storage Integration: Experience mounting high-performance parallel file systems (VAST/Lustre/WEKA/GPFS) and tuning client-side performance.
- Certifications:
- NVIDIA Certified Associate - AI in the Data Center.
- Red Hat Certified Engineer (RHCE).
- CKA (Certified Kubernetes Administrator).

Success Metrics (KPIs)

1. Deployment Velocity: Reduction in "Time-to-Hello-World" (time from power-on to running the first successful GPU job) for recent clusters.
2. Code Quality: >95% of Pull Requests pass automated linting and require fewer than 2 review cycles before merge.
3. Stability: Zero "Configuration Drift" incidents in production (e.g., manual changes breaking the cluster) due to strict IaC enforcement.

📌 Senior HPC Engineer (India)
🏢 World Wide Technology Holding
📍 India