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# Systems Engineering Lead, Servers, Clusters & Supercomputers

- **Company:** StaffRight Associates
- **Location:** Durham, NC, United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Systems Engineering, Computer Clusters, Computer Networks, Linux, File Systems, Distributed Systems, Python (Programming Language), Linux System Administration, Remote Direct Memory Access, Scientific Computating, Software Engineering, Supercomputing, Scripting, Graphics Processing Unit (GPU), Parallel Computation, Kubernetes, Slurm, Network Server
- **Published:** November 12, 2026
- **Apply:** https://www.dice.com/job-detail/82e0c64b-9e58-4a41-a8f2-8e32ea26484c

## About the Role

* Strong grounding in Linux fundamentals, including File Systems, Networking, and Processes, plus hands-on Linux Systems Administration experience.
 * Ability to explain technical reasoning to experts and non-specialists alike.
 * Five or more years of relevant experience.
 * A background in leading and managing engineering teams (helpful, not required).
 * Expertise in any of the following: Large-Installation Systems Administration, HPC Systems Engineering, Python programming and scripting for Distributed Systems, High-Performance Data-Parallel Computing, Systems Software, Software Development, and Security Tool Deployment.
 * The client weighs versatility, intellectual curiosity, and a record of strong accomplishment more heavily than depth in any single area above.

## Description

* Lead the engineering groups responsible for building and running the client's compute clusters and the software stack on top of them.
 * Direct the operation of Linux clusters scheduled with Slurm and Kubernetes, at scales from the low thousands of cores into the tens of thousands.
 * Scale GPU clusters numbering hundreds of GPUs and storage systems holding tens of petabytes of research data.
 * Sustain specialized, massively parallel custom supercomputing hardware alongside the general-purpose clusters.
 * Architect high-performance RDMA fabrics, wide-area networking, and public cloud environments.
 * Support the large-scale scientific workflows behind the client's drug discovery research.
 * Deliver all of these resources to researchers in a form that is both secure and easy to use.
 * Communicate clearly with research users and fellow engineers about priorities, tradeoffs, and system health., Candidates whose graduate or doctoral work centered on high-performance or distributed computing, operating systems, computer networking, or large-scale scientific computing in fields such as Computational Physics or Computational Chemistry will find that training maps closely onto this work.