# AI  Storage Engineer at DAMAC

DAMAC is hiring an AI  Storage Engineer. Level rates it Works on AI ●●●○; you can [apply on DAMAC](https://jobsbylevel.com/go/bc27f5ba-b77a-4ec4-9687-e46f85d62fa9?utm_medium=ai-agent).

AI Level 3, AI centrality 65 out of 100. Thailand.

## Details

- Company: [DAMAC](https://jobsbylevel.com/companies/damac)
- AI level: AI Level 3 (score 65 out of 100)
- Location: Thailand
- Posted: November 2, 2026
- Apply: https://jobsbylevel.com/go/bc27f5ba-b77a-4ec4-9687-e46f85d62fa9?utm_medium=ai-agent
- Free CV review for this job: https://jobsbylevel.com/cv-review?job=ai-storage-engineer-at-damac-76efc7

## Prepare for this job

The job page lists 3 likely interview questions for this offer, with a CV checklist: https://jobsbylevel.com/jobs/ai-storage-engineer-at-damac-76efc7

## Description

As AI Storage Specialist, you will own the design, deployment and optimisation of high-performance storage systems that underpin DAMAC Digital's AI GPU clusters. You will work across parallel file systems, NVMe tiers, object storage and archival layers — engineering the data path from ingest to checkpoint, and ensuring our NVIDIA Blackwell and Hopper platforms operate at their designed throughput. This is a hands-on architect role: you will lead solution design, drive vendor engagements, run PoCs and benchmarks, and partner closely with networking, compute, facilities and managed-services teams across our international sites. Architecture & Design Architect end-to-end storage solutions for large-scale AI training and inference clusters (NVIDIA DGX/HGX, SuperPOD, B300, GB300) Design tiered data pipelines: ingest → NVMe hot tier → warm object → cold/archive Integrate storage with GPUDirect Storage (GDS), NFS over RDMA, and InfiniBand/RoCE fabrics Produce HLDs, LLDs, BoMs and technical documentation to enterprise standards Deployment & Operations Deploy and manage parallel/distributed file systems — WEKA, VAST Data, DDN EXAScaler, Scale (GPFS), Lustre, BeeGFS Configure multi-tenant storage for sovereign cloud and managed AI services Implement checkpointing, snapshot, replication and DR strategies for AI workloads Performance & Benchmarking Benchmark storage throughput, IOPS and latency using IO500, MLPerf Storage and fio Tune systems for LLM training checkpoints, RAG pipelines and inference serving Capacity planning, growth modelling and cost-per-TB optimisation Vendor & Stakeholder Management Lead vendor evaluations, PoCs and commercial negotiations with storage OEMs Partner with NVIDIA, VAST, WEKA, DDN, Pure Storage and Dell technical teams Present designs and progress to internal leadership and enterprise customers REQUIRED QUALIFICATIONS Experience: 7+ years in enterprise storage, with a minimum of 2 years in AI, HPC or GPU-cluster environments File Systems: Deep expertise in one or more of WEKA, VAST Data, DDN, GPFS, Lustre, BeeGFS Protocols: GPUDirect Storage, NFS over RDMA, SMB, S3, NVMe-oF Networking: Working knowledge of InfiniBand (NDR/HDR) and RoCEv2 storage fabrics Platforms: Hands-on with NVIDIA reference architectures (DGX, HGX, SuperPOD, BasePOD) Automation: Linux administration, Python/Bash scripting, Ansible or Terraform Soft Skills: Strong documentation, stakeholder communication and vendor management PREFERRED QUALIFICATIONS Vendor certifications from VAST DATA, WEKA, DDN, or Pure Storage NVIDIA-Certified Associate — AI Infrastructure & Operations Experience with multi-tenant sovereign cloud or AI-as-a-Service platforms Exposure to Kubernetes CSI drivers, Slurm, and Run:ai orchestration Familiarity with data governance, encryption at rest, and cross-site replication Prior experience deploying at Tier III+ data centres in the Middle East or APAC

Source: https://jobsbylevel.com/jobs/ai-storage-engineer-at-damac-76efc7

## Cite this page

Level. https://jobsbylevel.com/jobs/ai-storage-engineer-at-damac-76efc7.

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