Staff Engineer in Test

Data Direct Networks • San Francisco - Remote, CA

15h • Remote

About The Position

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. DataDirect 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 is the global leader in AI and multi-cloud data management at scale. Our 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. We are seeking a highly skilled and technically strong Staff Engineer in Test to lead system level quality engineering efforts for networking, security and other enterprise readiness aspects of Infinia, DDN’s large-scale distributed data platform. In this role, you will be a senior technical authority responsible for planning and implementing test strategies and test infrastructures to ensure correctness, stability, performance, and resilience of Infinia’s distributed architecture. You will work across core subsystems—including the I/O path, memory management, networking stack, scheduling layers, multi-tenant services, and NVMe-backed storage patterns—to ensure platform quality at scale. This is a hands-on, high-impact IC role for someone who can solve hard problems, automate at scale, leverage AI to improve velocity and elevate quality engineering across the organization.

Requirements

• 10+ years of experience in software quality engineering, with strong focus on distributed systems, system-level testing, or infrastructure platforms .
• Hands-on expertise in test automation using Python , Bash , and modern CI/CD tooling (Git, Jenkins, etc.).
• Strong understanding of: Distributed concurrency
• File systems and I/O stack behavior
• Storage performance analysis (NVMe, SPDK)
• Networking, tracing, and system observability
• Experience with large-scale performance testing, stress testing, and reliability validation.
• Demonstrated skill in diagnosing complex system issues across logs, traces, network captures, and profiling tools.
• ISTQB or equivalent certification preferred.

Nice To Haves

• Experience validating large-scale data platforms , storage engines, or distributed scheduling systems.
• Experience with AI technologies in context of quality engineering, such as issue triaging, test generation, automation.
• Familiarity with observability technologies such as OpenTelemetry, Grafana, Prometheus .
• Background in compliance or security testing (e.g., access control, backup/restore workflows, Section 508/HIPAA/PCI).
• Contributions to open-source test frameworks or distributed systems validation tools.

Responsibilities

• Design detailed test strategies and validation plans for networking and security features for distributed system
• Create scalable, automated test suites that validate multi-tenant behavior, concurrency, data consistency, and system-level performance.
• Build and maintain robust automation using tools such as Pytest and container-based environments leveraging Docker, Jenkins, Kubernetes.
• Develop reusable automation templates, harnesses, and utilities to accelerate test creation and reduce engineering overhead.
• Construct and execute performance tests covering I/O throughput, system latency, NVMe access patterns, concurrency limits, and long-running workload stability.
• Use advanced tools (profilers, fuzzers, failure-injection frameworks, trace analyzers) to uncover issues in distributed workflows.
• Analyze CPU, memory, disk, and network utilization to diagnose performance bottlenecks and identify regression risks.
• Work closely with architects, developers, release engineering, DevOps, and customer engineering to drive quality-first design decisions.
• Participate in feature design reviews, ensuring testability, observability, and resilience are built into system components.
• Lead root cause analysis (RCA) for complex issues and propose long-term improvements to engineering practices and platform stability.
• Produce clear, detailed test plans, automation guides, design-review feedback, and quality metrics reports.
• Contribute to the development and maintenance of internal QA standards, best practices, and onboarding materials.

Benefits

• engineering excellence is at the heart of everything we do
• opportunity to work across various areas of the company, thanks to our flat organizational structure that encourages hands-on involvement and direct contributions to our mission
• Leadership is earned by those who take initiative and consistently deliver outstanding results, both in their work ethic and deliverables, making strong prioritization skills essential
• strong communication skills in all our engineers and researchers, as they are crucial for the success of our teams and the company as a whole

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed