Staff Infrastructure Engineer – Storage Platform
About TensorWave
Our mission is simple: deliver seamless, secure, reliable, and resilient AI compute at scale. We've built a versatile cloud platform that eliminates infrastructure barriers, empowering builders to focus on innovation instead of fighting their stack. Because breakthrough AI should move at the speed of ideas, not infrastructure.
About the Role
We are building and operating large-scale infrastructure platforms to support high-performance AI and machine learning workloads across multiple data centers. Our environment includes GPU-intensive systems, high-throughput networking, and distributed storage platforms that must deliver consistent performance at scale.
We are looking for a Staff Infrastructure Engineer – Storage Platform to own the design, operation, and evolution of our storage systems. This role combines architecture and hands-on operational ownership, ensuring that storage platforms are both well-designed and reliably executed in production.
You will be responsible for defining how storage works across the organization while remaining deeply involved in real-world system behavior, performance tuning, and incident response.
What You’ll Do
Architecture & Platform Design
Design and evolve storage architectures supporting Kubernetes (block, file, object storage), AI/ML and high-performance compute workloads
Evaluate and select storage technologies based on performance (IOPS, throughput, latency), scalability and fault tolerance, operational complexity and maintainability
Define storage standards, best practices, and reference architectures
Design for resilience over traditional HA, including failure-domain awareness
Platform Ownership & Operations
Own production storage platforms, including Ceph (RBD, CephFS, RGW), High-performance NAS (Weka, VAST, or similar)
Lead lifecycle operations - Cluster design and deployment, expansion and scaling, upgrades and migrations
Perform and guide capacity planning, performance tuning, failure analysis
Performance & Reliability
Analyze storage performance across IOPS, throughput, latency, and tail latency
Identify and resolve bottlenecks across disk subsystems, network paths (including RDMA), client access patterns
Lead root cause analysis for storage-related incidents
Ensure storage platforms meet the demands of GPU and Kubernetes workloads
Kubernetes Storage Integration
Define and implement Kubernetes storage patterns - CSI drivers, StorageClasses, persistent storage design
Troubleshoot complex Kubernetes storage issues involving stateful workloads, provisioning failures, performance anomalies
Partner with platform teams to align storage with workload requirements
Automation & Tooling
Design and implement automation for storage deployment and configuration, cluster lifecycle management
Leverage tools such as Ansible, Terraform, Kubernetes manifests / Helm
Integrate storage platforms into observability stacks (Prometheus, Grafana, etc.)
Technical Leadership
Serve as the technical authority for storage across the organization
Mentor engineers on storage systems, performance, and troubleshooting
Establish operational standards and best practices
Drive continuous improvement of storage reliability and performance
Who You Are
Required Qualifications
7+ years of experience in infrastructure, storage, or distributed systems
Deep hands-on experience with distributed storage systems in production
Strong experience with Ceph (RBD, CephFS, and/or RGW)
Experience with high-performance storage platforms such as:
Weka, VAST Data, or similar
Strong understanding of:
Storage performance characteristics
Data replication and failure domains
Distributed system design principles
Strong Linux systems expertise
Ability to troubleshoot across:
Storage, network, and compute layers
Preferred Qualifications
Experience supporting AI/ML or HPC workloads
Familiarity with:
NVMe-based architectures
RDMA or high-throughput Ethernet
Experience integrating storage with Kubernetes at scale
Experience operating across multiple data centers
Exposure to object storage and S3-compatible APIs
What We Offer
Stock Options
100% paid Medical, Dental, and Vision insurance for Employees
Company Health Savings Account Contributions
100% paid Short Term and Long Term Disability Insurance for Employees
Life and Voluntary Supplemental Insurance Options
Other Insurance Options, such as Pet & Legal Insurance
Various Supplementary Health Benefits, such as discounted Virtual Healthcare Appointments and Serious Illness Support
Flexible Spending Account
401(k)
Employee Assistance Program
Flexible PTO
Paid Holidays
Parental Leave
Other In-Office Perks
Equal Employment Opportunity
TensorWave is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate on the basis of any protected status under applicable law.
Reasonable Accommodations
TensorWave provides reasonable accommodations in accordance with applicable laws. If you require accommodation during the hiring process, please contact [email protected].
Employment Eligibility
All offers of employment are contingent upon verification of identity and authorization to work in United States, as required by law.
Background Checks
Where permitted by law, employment may be contingent upon the successful completion of a job-related background check.
Data Privacy Notice
By submitting an application, you acknowledge that TensorWave may collect, use, and retain your personal information for recruiting and employment-related purposes in accordance with applicable data privacy laws.