AI Infrastructure Solutions Engineer

About the role

DDN is expanding its enterprise AI offerings by integrating industry-leading technologies with DDN Infinia and DDN EXAScaler storage, optimized for inference and RAG workloads. The support organization is deep in storage and is hiring an AI Infrastructure Solutions Engineer to deploy these complete AI solutions, remotely or onsite in some cases, and to customize them to customer requirements. The engineer works with internal teams, vendors and partners to deliver the solutions.

Key responsibilities

• Serve as the primary technical point of contact for strategic customers deploying DDN AI solutions
• Work with pre-sales to interpret design considerations during solution deployment
• Drive operational efficiency through automation, tooling, documentation and repeatable deployment workflows
• Develop and deploy DevOps-focused scripts and tools for customer environments, including monitoring and metrics tools
• Support AI/ML, data-intensive and HPC workloads at scale in on-premises, hybrid and cloud-adjacent environments
• Work with customers to optimize their AI applications for DDN technology

Required profile

• 5+ years of experience in a senior technical role deploying complex, customer-facing production systems
• Experience administering and operating Lustre or similar parallel file systems in large-scale environments
• Experience with object storage and S3-compatible systems
• Strong Linux systems knowledge, including performance tuning and troubleshooting
• Solid understanding of distributed storage architectures, networking fundamentals and data movement at scale
• Proven ability to work directly with customers and build trusted technical relationships

Required skills

• Preferred: additional parallel file systems such as IBM Spectrum Scale or StorNext
• Preferred: automation scripting in shell, Python or Bash
• Preferred: networking technologies including InfiniBand, Ethernet, TCP/IP and routing
• Preferred: NVAIE services (NIMs, NeMo, Triton, TensorRT, GPU Operator, licensing) and vector databases such as Milvus
• Preferred: NAS protocols (NFS, SMB/CIFS, SFTP, rsync), identity systems (LDAP, AD, Kerberos, OAuth2/OIDC, SAML) and network diagnostics tools (tcpdump, Wireshark)
• Preferred: Kubernetes, SLURM, BCM and remote team experience