Systems & Platform Engineer - TS/SCI

Sunayu•Bethesda, MD

22h•Onsite

About The Position

Sunayu, LLC is seeking a highly skilled platform engineer with deep expertise in operating systems, hardware, GPU, and high-speed networking. In this role, you will design, develop, and optimize Kubernetes clusters that power enterprise AI for mission customers. This is a 100% on-site position, requiring all work to be performed at the customer site in Bethesda at the Intelligence Community Campus.

Requirements

Bachelor's or higher degree in Computer Science, Electrical Engineering, or a related field. Additional years of experience may be considered in lieu of a degree.
5+ years in Platform Engineering or System Engineering experience.
Strong expertise with Linux distributions (RHEL, Ubuntu, Oracle Linux, and Rocky).
Experience administering Kubernetes clusters, including deploying, scaling, and maintaining containerized workloads.
Hands-on experience creating, managing, and troubleshooting Docker containers and container images throughout the software development lifecycle.
Experience with Kubernetes cluster management and AI/ML workflow orchestration (Argo, Airflow, and Kubeflow).
Strong track record with consuming, and troubleshooting RESTful APIs for platform integration and automation.
Excellent problem-solving skills and the ability to collaborate within a team.
Candidate must, at a minimum, meet DoD 8570.11- IAT Level II certification requirements (currently Security+ CE, CCNA-Security, GICSP, GSEC, or SSCP along with an appropriate computing environment (CE) certification). An IAT Level III certification would also be acceptable (CASP+, CCNP Security, CISA, CISSP, GCED, GCIH, CCSP).
Active TS/SCI clearance with Polygraph required OR active TS/SCI and willingness to obtain and maintain a Poly.
US Citizenship is required.

Nice To Haves

Experience in managing NVIDIA GPU data center platforms (DGX, HGX, H200, H100, 200, B300, L40S).
Experience with NVIDIA enterprise tools such as Base Command Manager, Run:AI, Nvidia AI Enterprise.
Knowledge of enterprise server components (storage/network controllers, HBA, SSDs).
Familiarity with GPU virtualization and cloud computing.
Experience developing and deploying infrastructure in AWS.
Knowledge of distributed resource scheduling systems (Slurm, LSF, Open MPI, etc.).

Responsibilities

Design, configure, and maintain enterprise Kubernetes platforms.
Collaborate with a multidisciplinary team to define and optimize Kubernetes architecture, ensuring they meet performance, efficiency, and feature requirements.
Develop and manage Infrastructure as Code (IaC) using tools such as Terraform, Salt, Ansible, Bash, Python or similar frameworks.
Collaborate with development teams to design and implement secure, automated, and repeatable pipelines (e.g., GitLab CI/CD).
Troubleshoot complex systems issues across cloud, network, and platform layers.
Maintain technical documentation, architectural specifications, and Linux best practices.
Support ATO (Authority to Operate) and ensure compliance with federal security standards.