Principal Performance Architect

April 25

Apply Now

Receive Emails with Similar Jobs

DDN

WebsiteLinkedInAll Job Openings

DDN is a global leader in AI data intelligence platforms, providing high-performance data management solutions designed to optimize and accelerate AI and computing tasks. With over two decades of experience, DDN specializes in delivering cutting-edge technology for data-intensive applications across various industries, including healthcare, financial services, and telecommunications. Their comprehensive solutions include state-of-the-art hardware and software systems that empower enterprises to effectively manage complex datasets and drive innovation through artificial intelligence.

Artificial Intelligence • Data Storage • Machine Learning • Analytics • Enterprise AI

1001 - 5000 employees

Founded 1998

🤖 Artificial Intelligence

💳 Fintech

💰 $10M Funding Round on 2011-06

📋 Description

• DDN is seeking a Principal Performance Architect to drive end-to-end performance analysis and optimization for Infinia, our AI-native, highly distributed data intelligence platform. • In this critical role, you will own the visibility, measurement, and tuning of system performance across the entire stack — from AI applications, vector databases, and inference pipelines, down to I/O patterns on NVMe drives. • You’ll partner with teams across engineering, architecture, and field engineering to deliver insights and innovations that drive customer value at scale. • This is a hands-on, full-stack systems performance role — ideal for someone who thrives on pushing the boundaries of scale, throughput, and latency across deeply interconnected layers.

🎯 Requirements

• 15+ years of experience in systems performance engineering or low-level infrastructure development. • Proven expertise in end-to-end performance debugging across distributed systems, from application logic down to I/O subsystems. • Strong background in system-level tools (e.g., perf, ftrace, bpftrace, nvme-cli, or similar). • Deep understanding of NVMe, CPU and memory hierarchy, caching, thread scheduling, and Linux kernel internals. • Experience optimizing compute- or data-intensive applications such as AI inference, search, or analytics. • Proficiency in C/C++ or Rust and scripting languages such as Python or Bash. • Excellent written and verbal communication skills, especially around technical reporting and architectural recommendations.