Systems Development Engineer 2 (PowerScale)

On-site
CompanyDell
LocationTaipei City, Taiwan
CategorySoftware Engineering
Seniority-
WorkplaceOn-site
Posted2026-07-30
Viaoracle

Description

Systems Development Engineer 2 (PowerScale)

Our customers operate highly complex, mission-critical environments that demand deep technical expertise across hardware, software, and full-system architecture. As part of the Customer Engineering team, you will work at the intersection of system design, advanced diagnostics, and performance engineering. This includes analyzing integrated electronic and electro-mechanical systems, conducting feasibility and architecture evaluations, and developing specifications that ensure robust, predictable system behavior.

The Customer Engineering Team focuses on advanced root-cause analysis, performance optimization, configuration tuning, and long-term stability improvements. You will tackle the toughest technical challenges in enterprise environments—driving solutions that improve reliability, scalability, and overall system efficiency for global customers.

Join us as a Systems Development Engineer 2 (Escalating Engineer) on our Customer Engineering Team in Taipei, Taiwan.

What You’ll Achieve

As a Systems Development Engineer 2, you will:

Key Responsibilities

  • Collaborate with core engineering teams, Customer Support, Incident Management, and customers to troubleshoot, stabilize, and optimize enterprise environments.
  • Perform advanced troubleshooting, root cause analysis (RCA), and kernel-level debugging across distributed software systems, enterprise infrastructure, and supported operating systems running on Dell hardware.
  • Leverage expertise in computer architecture and operating system internals to resolve complex technical issues, improve system resilience, and provide actionable recommendations to internal and external stakeholders.
  • Document technical findings and effectively communicate insights, resolutions, and strategic recommendations to both technical and executive audiences.
  • Build strong cross-functional partnerships to drive collaborative problem-solving and operational excellence.
  • Design and implement intelligent automation solutions using AI and emerging agentic technologies to improve productivity, efficiency, and service reliability.
  • Contribute to strategic initiatives that enhance operational efficiency, resilience, and scalability across the organization.

Requirements

  • Work Model: Onsite, 5 days a week ( remote/hybrid not eligible ).
  • Schedule: Weekend work on a rotational basis (comp days provided), occasional early/late shifts, and overtime as needed.

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Experience

  • 3+ years in software/hardware engineering (or equivalent) with deep expertise in one or more of the following:
  • NAS storage
  • Clustered and Scale-out Filesystems (Quotas, Data Reduction, Locking)
  • Performance
  • Protocols (SMB, NFS, S3,etc.)
  • Networking
  • Linux/BSD operating systems
  • Replication
  • Technical Skills:
  • Hands-on troubleshooting experience with NAS storage platforms and distributed storage architectures.
  • Understanding data replication, resiliency, performance optimization, and storage protocols.
  • Strong knowledge of TCP/IP, DNS, HTTP/HTTPS, load balancing, proxies, and network troubleshooting.\
  • Performance troubleshooting
  • Ability to analyze application logs, thread dumps, heap dumps, garbage collection behavior, and performance bottlenecks.
  • Experience supporting and debugging REST APIs and service integrations.
  • Understanding of authentication mechanisms, authorization flows, API gateways, and service communication patterns.
  • Strong Linux administration and debugging experience.

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Ability to investigate processes, memory, CPU, filesystem, networking, and performance-related issues using standard Linux/BSD diagnostic tools.

  • Desirable Qualifications:
  • Proficiency in Java, C, Python , and scripting
  • Proven experience in developing automation frameworks and applying AI/agentic tools to drive operational efficiency and scalability