Senior Storage Production Engineer - DGX Cloud

Description

The role is a production engineering position on the team that runs the company's internal and external GPU cloud services. Production engineers build, run and maintain large production systems, with a focus on efficiency and availability.

Work covers storage architecture, high-performance distributed storage, data management, systems, networking, coding, databases, continuous delivery, and cloud technologies such as Kubernetes, containers and virtualization. The job includes keeping storage designs reliable, scalable and efficient, placing and accessing data well, and running large distributed storage systems with low latency for HPC and AI/ML workloads.

The goal is to meet the uptime and reliability commitments made to users while letting developers change the system safely through careful planning, with attention to capacity, latency and performance. Much of the software work automates operations, speeds up system response and improves storage efficiency. Because production engineers see how the systems connect, they use a range of tools. Proactive performance monitoring, automated fault detection and repair, scalable redundancy and intelligent caching drive ongoing improvements to reliability and efficiency.

The base salary range is 176,000 USD to 276,000 USD for Level 4 and 208,000 USD to 333,500 USD for Level 5. Pay depends on location, experience and the pay of people in similar roles.

Responsibilities

• Design, build and support large storage clusters that scale, stay highly available and keep data intact.
• Build and maintain storage monitoring, logging and alerting so performance problems are found and fixed early.
• Improve storage designs for AI/ML workloads, covering low-latency access, efficient caching and high throughput.
• Own storage services across their life, from design and deployment through operation and ongoing tuning. Help before launch with system build consulting, automation frameworks, capacity planning and launch reviews.
• Keep production storage healthy by watching availability, latency and system health, using predictive analytics and AI-driven automation.
• Improve storage efficiency with compression, deduplication, tiering and smart workload placement.
• Scale storage using AI/ML automation, policy-based tiering and dynamic data migration. Add encryption, access controls and auditing to protect data and meet compliance needs.
• Respond to incidents in a sustainable way and run blameless root cause analysis. Take part in the on-call rotation for storage and production systems.

Requirements

• A BS degree or equivalent experience in computer science, storage systems or a related technical field, plus 8+ years of hands-on experience.
• Experience with distributed and high-performance storage, including clustered and parallel file systems, distributed object storage and enterprise storage systems.
• A solid grasp of block, file and object storage, including how each scales, its reliability and performance traits, and standard practices.
• Experience with storage networking protocols such as NFS, SMB, iSCSI, S3, Fibre Channel, RDMA and NVMe over Fabrics.
• Strong knowledge of algorithms, data structures, complexity analysis and software design, and experience automating upkeep of large Linux storage systems.
• Experience with one or more of C/C++, Java, Python, Go, NodeJS and Bash for storage automation, monitoring and performance tuning.
• Hands-on experience with configuration management tools such as Ansible, Chef, Puppet and Terraform for automating storage deployments, and with observability tools such as InfluxDB, Prometheus, Grafana and the Elastic stack.
• Excellent written and spoken communication, strong work ethic, a team mindset, a commitment to quality and the discipline to finish tasks every day.

Conditions

Applications are accepted until at least October 30, 2026.

This posting is for an existing vacancy.

The company uses AI tools in its recruiting process.

The company is committed to an inclusive workplace and is an equal opportunity employer, and does not discriminate on protected characteristics.

Benefits

• Standing out from other candidates is helped by the following: deep knowledge of large distributed storage systems, replication strategies and erasure coding; experience with capacity planning, performance tuning and troubleshooting high-throughput storage; experience with Git, code review, pipelines and CI/CD for infrastructure as code; strong systematic debugging; understanding of network protocols as they affect storage performance, stability and availability; experience with private or public cloud storage built on Kubernetes, OpenStack or hybrid cloud; ability to design automated storage migration, backup and disaster recovery; comfort working across teams; and flexibility with new storage technologies and working styles.