Our Partner company, Vexterra Group, is looking for 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 the mission customers. The work location is in Bethesda at the Intelligence Community Campus. Primary Responsibilities Kubernetes Cluster Engineering: 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. Infrastructure as Code: 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). Troubleshot complex systems issues across cloud, network, and platform layers. Compliance & Documentation: Maintain technical documentation, architectural specifications, and Linux best practices. Support ATO (Authority to Operate) and ensure compliance with federal security standards.
QualificationsBasic Qualifications
• Requires a Bachelor’s degree and 10+ years of relevant experience, or Masters degree with 8+ years of experience. 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).
Security Clearance: TS/SCI with CI Poly is required for position or a TS/SCI and willingness to obtain a Poly. Preferred Qualifications
• 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
Additional InformationAll your information will be kept confidential according to EEO guidelines.
Skills Required
- Bachelor's degree and 10+ years of relevant experience, or a master's degree and 8+ years of experience; additional experience may substitute for a degree
- 5+ years of platform engineering or systems engineering experience
- Strong expertise with Linux distributions, including RHEL, Ubuntu, Oracle Linux, and Rocky Linux
- Experience administering Kubernetes clusters, including deploying, scaling, and maintaining containerized workloads
- Hands-on experience creating, managing, and troubleshooting Docker containers and images throughout the software development lifecycle
- Experience with Kubernetes cluster management and AI/ML workflow orchestration using Argo, Airflow, and Kubeflow
- Experience consuming and troubleshooting RESTful APIs for platform integration and automation
- DoD 8570.01 IAT Level II or Level III certification, including an appropriate computing environment certification
- TS/SCI with CI Poly, or TS/SCI with willingness to obtain a polygraph
- Experience managing NVIDIA GPU data center platforms such as DGX, HGX, H200, H100, B300, or L40S
- Experience with NVIDIA Base Command Manager, Run:AI, or NVIDIA AI Enterprise
- Knowledge of enterprise server components, including storage and network controllers, HBA, and SSDs
- Familiarity with GPU virtualization and cloud computing
- Experience developing and deploying infrastructure in AWS
- Knowledge of distributed resource scheduling systems such as Slurm, LSF, or Open MPI
What We Do
We are an engineering company that has been providing extensive support to Federal Government clients in global communications and networks, Cyber, Artificial Intelligence, Automation, and Analytics technologies for more than 16 years.








