Sobre este puesto de Engineer, Storage and Data Protection en Thinkahead
Key Responsibilities
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Provide enterprise-level operational support to Managed Services customers for incident, problem, and change management activities
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Administer parallel and distributed filesystems such as Lustre, GPFS, BeeGFS, Ceph, Weka, or Vast
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Optimize storage performance, throughput, metadata operations, and data locality for AI training and inference
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Build and maintain automation for storage provisioning, monitoring, alerting, quota management, and lifecycle operations
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Plan and perform maintenance activities
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Assess customer environments for performance and design issues and propose resolutions
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Work across technical teams to troubleshoot complex infrastructure issues
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Create and maintain detailed documentation
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Serve as a subject matter expert and escalation point for storage technologies
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Work with vendors to resolve storage issues
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Communicate with customers and internal team with transparency
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Support data movement workflows including ingest, replication, caching, tiering, and archiving
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Troubleshoot storage, Linux, network, and I/O bottlenecks across storage clusters and fabrics
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Partner with infrastructure, platform, and research teams to support production AI/HPC workloads
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Evaluate new storage architectures and technologies for scalability, resilience, and cost efficiency
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Communicate with customers and internal team with transparency
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Participate in on-call rotation
Required Qualifications
5+ years of experience with HPC, AI infrastructure, or large-scale storage engineering
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Bachelor’s degree or equivalent Information Systems or related field. Unique education, specialized experience, skills, knowledge, training, or certification may be substituted for education
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Strong experience with Linux systems administration
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Hands-on experience configuring, managing, and tuning distributed or parallel filesystems
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Experience tuning storage for performance-sensitive workloads
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Knowledge of HPC schedulers such as Slurm and/or container platforms such as Kubernetes
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Familiarity with high-speed interconnects such as InfiniBand or RDMA
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Ability to troubleshoot complex issues across storage, compute, and networking layers
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Understanding of data protection mechanisms, including data replication, backup strategies, and disaster recovery in HPC environments
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Experience with machine learning or data science workflows in HPC environments
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Managed Services or consulting experience
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Strong background with customer service
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High level problem-solving and communication skills
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Strong oral and written communications skills
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Managed Services or consulting experience
Preferred Qualifications
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Experience supporting storage solutions for GPU clusters and AI/ML workflows
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Familiarity with object storage such as S3, MinIO, or Ceph Object Gateway
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Experience with Terraform, Ansible, Helm, or GitOps workflows
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Knowledge of observability platforms such as Prometheus and Grafana
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Experience with multi-petabyte environments, caching architectures, and storage isolation in multi-tenant systems
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Experience with machine learning or data science workflows in HPC environments
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Scripting or programming experience with Python and Bash
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Related Storage certifications are a bonus
