Role: Production Engineer - AI Storage & HPC Infrastructure
Location: United States, Pacific time zone preferred
Work Type: Remote-first, with occasional on-site visits to customer offices.
Salary:$110K to $150K per annum
We are seeking a highly skilled Production Engineer - AI Storage & HPC Infrastructure to support and Eligible to workimize next-generation AI and High-Performance Computing (HPC) environments.
In this role, you will help build, operate, and scale high-performance storage platforms that support large-scale machine learning, AI training, advanced analytics, and distributed computing workloads. The ideal candidate will combine expertise in storage systems, Linux, automation, performance engineering, and infrastructure operations to ensure reliable and efficient access to critical datasets and model artifacts across enterprise-scale environments.
This is a hands-on engineering role involving storage architecture, performance Eligible to workimization, automation, observability, and production support.
Key Responsibilities
Required Skills & Experience
Strong experience designing, operating, or supporting large-scale distributed storage platforms, high-performance file systems, or enterprise data infrastructure.
Deep hands-on Linux administration and troubleshooting experience.
Strong understanding of file systems, storage protocols, networking, concurrency, and performance Eligible to workimization.
Experience diagnosing production issues related to storage performance, data access, throughput bottlenecks, and system reliability.
Hands-on programming or automation experience using one or more of the following:
Python
Go
C++
Rust
Experience driving end-to-end reliability improvements, performance Eligible to workimization initiatives, or large-scale operational enhancements.
Strong debugging, analytical, and problem-solving skills.
Experience working in highly available production environments with operational ownership responsibilities.
Qualifications:
Experience with Kubernetes, container orchestration platforms, and cloud-native infrastructure.
Strong understanding of distributed filesystem concepts including metadata management, caching, consistency, failover, recovery, and high availability.
Hands-on experience with one or more enterprise storage technologies such as:
Lustre
ZFS / OpenZFS
VAST Data
Pure Storage
Hammerspace
Similar large-scale distributed storage platforms
Experience supporting AI, Machine Learning, Data Engineering, or HPC infrastructures.
Understanding of high-throughput data ingestion, checkpoint management, data staging, and accelerator-cluster storage requirements.
Experience with Infrastructure as Code (IaC) and automation tools including:
Terraform
Helm
Kubernetes Operators
Experience implementing observability and monitoring solutions using metrics, logging, tracing, benchmarking, and capacity-planning tools.
Familiarity with object storage technologies, S3-compatible storage, lifecycle management, tiering, replication, and cross-region data movement.
Preferred Profile
Disclaimer: Diverse Lynx LLC is an Equal Opportunity Employer. All applicants and employees are evaluated without discrimination, based solely on their qualifications, ability, competence and performance. This email and its attachments may contain confidential or proprietary information and is intended only for the recipient(s). If you received this message in error, please disregard it and notify the sender. If you no longer wish to receive our communications, you may unsubscribe at any time.
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| Location | San Jose, CA (Remote) |
| Salary | $110,000–$150,000 Per Year |
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