Principal Performance Architect

Overview

This is an incredible opportunity to be part of a company that has been at the forefront of AI and high-performance data storage innovation for over two decades. Data Direct Networks (DDN) is a global market leader renowned for powering many of the world's most demanding AI data centers, in industries ranging from life sciences and healthcare to financial services, autonomous cars, Government, academia, research and manufacturing.

"DDN's A3I solutions are transforming the landscape of AI infrastructure." – IDC

“The real differentiator is DDN. I never hesitate to recommend DDN. DDN is the de facto name for AI Storage in high performance environments” - Marc Hamilton, VP, Solutions Architecture & Engineering | NVIDIA

DDN is the global leader in AI and multi-cloud data management  cutting-edge data intelligence platform is designed to accelerate AI workloads, enabling organizations to extract maximum value from their data. With a proven track record of performance, reliability, and scalability, DDN empowers businesses to tackle the most challenging AI and data-intensive workloads with confidence.

Our success is driven by our unwavering commitment to innovation, customer-centricity, and a team of passionate professionals who bring their expertise and dedication to every project. This is a chance to make a significant impact at a company that is shaping the future of AI and data management.

Our commitment to innovation, customer success, and market leadership makes this an exciting and rewarding role for a driven professional looking to make a lasting impact in the world of AI and data storage.

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.

We are looking for remote candidates in the following metropolitan areas:
Boston, MA;
Raleigh, NC;
Denver, CO; or Tucson, AZ. Occasional in-person meetings or team events may be required.

• End-to-End Performance Architecture:
  Design and implement comprehensive performance instrumentation across the Infinia platform — from AI pipelines to storage backends.
• Develop and maintain end-to-end performance models that span applications (e.g., LLM inference, vector search), query engines, data pipelines, and NVMe-backed storage.

• Profiling, Benchmarking & Bottleneck Analysis:
  Build and execute reproducible performance tests that simulate realistic AI and data-intensive workloads.
• Use advanced profiling and tracing tools (e.g., perf, eBPF, flame graphs, custom telemetry) to identify and address latency hotspots, bandwidth bottlenecks, and concurrency inefficiencies.
• Drive performance regression testing into CI pipelines and track key performance metrics over time.

• Collaboration & Optimization:
  Partner with component teams (I/O Path, Core Platform, Data Engine, and AI Applications) to deliver performance fixes and architectural recommendations.
• Work closely with hardware and storage teams to analyze I/O patterns on NVMe drives and optimize storage usage for real-world applications.
• Provide tuning guidance for AI/ML applications, vector databases, and orchestration layers to maximize system utilization and efficiency.

• Technical Leadership & Reporting:
  Own the performance roadmap and ensure performance visibility across teams and stakeholders.
• Deliver clear, actionable performance summaries to engineering, product management, and field teams.
• Mentor engineers on best practices in profiling, benchmarking, and performance-aware development.

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