Technical practice
HPC Cluster Orchestration with Slurm and Kubernetes
What to coverExplain how you manage the coexistence of Slurm and Kubernetes in a hybrid HPC/AI environment. Discuss the trade-offs between using Slurm for batch job scheduling versus Kubernetes for containerized AI workloads and how you handle resource contention.
Optimizing GPU Cluster Performance
What to coverDescribe your approach to tuning large-scale GPU clusters (e.g., H100/A100) for maximum utilization. Address strategies for managing multi-rail networking, InfiniBand/RoCEv2 configurations, and minimizing data bottlenecks during distributed training.
Infrastructure as Code (IaC) for HPC
What to coverHow do you apply Terraform and Ansible to automate the deployment of complex HPC environments? Focus on maintaining configuration baselines and ensuring reproducibility across production and non-production cloud environments.
High-Performance Storage Architectures
What to coverCompare parallel file systems like Lustre, GPFS, or BeeGFS in the context of AI training workloads. Discuss how you select a storage backend based on requirements for NVMe-oF, throughput, and latency.
Troubleshooting Low-Latency Networking
What to coverDetail your methodology for diagnosing performance degradation in high-speed fabrics like InfiniBand NDR. Suggest tools or metrics you use to identify congestion, packet loss, or misconfigured multi-planar designs.
Cost Optimization in Hybrid Cloud HPC
What to coverExplain your strategy for managing FinOps in a hybrid environment, specifically regarding Reserved Instances and Spot VM strategies. How do you balance cost efficiency with the high availability requirements of large-scale AI models?
Integrating MLOps with HPC Infrastructure
What to coverDescribe how you integrate tools like Kubeflow or MLflow into an existing HPC stack. Focus on how you enable data scientists to transition from development in Jupyter notebooks to large-scale distributed training on GPU clusters.
Agentic AI for Infrastructure Automation
What to coverHow might you leverage Agentic AI technologies to improve infrastructure observability or automated remediation? Suggest a practical use case where an autonomous agent could optimize cluster health or workload scheduling.
Behavioural practice
Managing Large-Scale Infrastructure Incidents
What to coverDescribe a situation where a critical failure occurred in a high-performance computing environment. Explain your role in the troubleshooting process, how you communicated with stakeholders, and the steps taken to ensure future resiliency.
Technical Guidance for Cross-Functional Teams
What to coverProvide an example of when you had to explain complex HPC architecture requirements to non-technical stakeholders or users. How did you ensure your technical guidance enabled them to execute their workloads efficiently?
Adapting to Rapidly Evolving AI Technologies
What to coverDescribe a time you had to quickly learn and implement a new AI infrastructure tool or framework to meet a project deadline. How did you validate the technology's suitability for a production environment?
Balancing Conflicting Project Priorities
What to coverDiscuss a scenario where you had to balance the immediate needs of a production AI workload with long-term infrastructure scalability goals. How did you prioritize tasks and manage expectations with the project team?