Production Engineer, AI Storage for HPC Clusters L2

The customer’s Cloud Foundation AI Services team builds and operates the storage that lets AI researchers train models reliably and efficiently across cloud environments.

We connect high-performance filesystems, object storage, and data-management services to AI compute, so training datasets and model checkpoints are fast and available wherever they are needed.

We are looking for a hands-on storage system engineer who can turn demanding AI workloads into reliable, scalable infrastructure. The work spans software development, performance analysis, automation, and production ownership.

What You’ll Do

• Build and operate distributed file and object storage for AI training: shared researcher filesystems, training datasets, and model checkpoints.
• Diagnose and improve end-to-end storage performance (metadata, throughput, latency, caching, network) so storage I/O stops stalling training.
• Automate the storage lifecycle (provisioning, scaling, upgrades, recovery) using Kubernetes and infrastructure-as-code.
• Move and migrate data across clusters, regions, and clouds without losing integrity or slowing researchers down.
• Keep it reliable through observability, alerting, testing, safe rollouts, and incident response, partnering with research, security, and storage-provider teams.

Must-Haves

• Built or operated production distributed storage, high-performance filesystems, or large scale data infrastructure.
• Strong Linux skills, and can debug filesystem, network, and concurrency issues in production.
• Writes maintainable software or automation in a language such as Python, Go, C++, or Rust.
• Has owned a reliability or performance improvement end to end, from spotting the problem through deployment and verification.

• Experience with cloud infrastructure and Kubernetes, or a comparable large-scale orchestration environment.
• Depth in NFS/POSIX and distributed-filesystem internals: metadata, caching, consistency, availability, and recovery.
• Hands-on with one or more distributed or network storage systems such as Hammerspace, Lustre, ZFS/OpenZFS, VAST, or Pure Storage. Depth in comparable systems counts; you do not need every product named here.
• AI or HPC storage patterns: high-throughput data loading, checkpoint writes and restores, metadata-heavy access, and staging data for accelerator clusters.
• Infrastructure-as-code and observability tooling (Terraform, Helm, Kubernetes operators; metrics, tracing, benchmarking), and object/S3 storage with tiering and cross-region movement.

Experience: >10 YEARS .

The expected compensation for this role ranges from $100,000 to $200,000 .

Final compensation will depend on various factors, including your geographical location, minimum wage obligations, skills, and relevant experience. Based on the position, the role is also eligible for Wipro’s standard benefits including a full range of medical and dental benefits options, disability insurance, paid time off (inclusive of sick leave), other paid and unpaid leave options.

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