Engineer, Storage and Data Protection

Key Responsibilities

 

• • Provide enterprise-level operational support to Managed Services customers for incident, problem, and change management activities 

• • Administer parallel and distributed filesystems such as Lustre, GPFS, BeeGFS, Ceph, Weka, or Vast 

• • Optimize storage performance, throughput, metadata operations, and data locality for AI training and inference 

• • Build and maintain automation for storage provisioning, monitoring, alerting, quota management, and lifecycle operations 

• • Plan and perform maintenance activities 

• • Assess customer environments for performance and design issues and propose resolutions 

• • Work across technical teams to troubleshoot complex infrastructure issues 

• • Create and maintain detailed documentation 

• • Serve as a subject matter expert and escalation point for storage technologies 

• • Work with vendors to resolve storage issues 

• • Communicate with customers and internal team with transparency 

• • Support data movement workflows including ingest, replication, caching, tiering, and archiving 

• • Troubleshoot storage, Linux, network, and I/O bottlenecks across storage clusters and fabrics 

• • Partner with infrastructure, platform, and research teams to support production AI/HPC workloads 

• • Evaluate new storage architectures and technologies for scalability, resilience, and cost efficiency 

• • Communicate with customers and internal team with transparency 

• • Participate in on-call rotation 

Required Qualifications

 

• • 5+ years of experience with HPC, AI infrastructure, or large-scale storage engineering 

• • Bachelor’s degree or equivalent Information Systems or related field. Unique education, specialized experience, skills, knowledge, training, or certification may be substituted for education 

• • Strong experience with Linux systems administration 

• • Hands-on experience configuring, managing, and tuning distributed or parallel filesystems 

• • Experience tuning storage for performance-sensitive workloads 

• • Knowledge of HPC schedulers such as Slurm and/or container platforms such as Kubernetes 

• • Familiarity with high-speed interconnects such as InfiniBand or RDMA 

• • Ability to troubleshoot complex issues across storage, compute, and networking layers 

• • Understanding of data protection mechanisms, including data replication, backup strategies, and disaster recovery in HPC environments 

• • Experience with machine learning or data science workflows in HPC environments 

• • Managed Services or consulting experience 

• • Strong background with customer service 

• • High level problem-solving and communication skills 

• • Strong oral and written communications skills 

• • Managed Services or consulting experience 

 

 

Preferred Qualifications 

 

• • Experience supporting storage solutions for GPU clusters and AI/ML workflows 

• • Familiarity with object storage such as S3, MinIO, or Ceph Object Gateway 

• • Experience with Terraform, Ansible, Helm, or GitOps workflows 

• • Knowledge of observability platforms such as Prometheus and Grafana 

• • Experience with multi-petabyte environments, caching architectures, and storage isolation in multi-tenant systems 

• • Experience with machine learning or data science workflows in HPC environments 

• • Scripting or programming experience with Python and Bash 

• • Related Storage certifications are a bonus