Cloud Solutions Engineer

About the Role

As a Cloud and Artificial Intelligence (AI) Infrastructure Administrator, you will implement and maintain cloud solutions in support of a national security mission to maintain the safety, security, and effectiveness of the United States nuclear weapons stockpile. Working as part of the Information Technology (IT) organization’s IT Infrastructure team, you will install, manage, and maintain a growing cloud-based infrastructure in a large, distributed network environment. You will also engineer and collaborate with IT project management and other IT Subject Matter Experts to implement new technologies, including those supporting AI solutions.

Responsibilities

• Install, configure, administer, manage, and support Software as a Service (SaaS) and Platform as a Service (PaaS) solutions running in both Azure and Amazon Web Services (AWS).
• Optimize buildouts of cloud solutions, including specialized infrastructure for AI/Machine Learning (ML) workloads.
• Design and engineer cloud solutions to meet customer requirements, with consideration for AI application performance and scalability.
• Deploy, configure, and manage Azure resources specifically designed for AI and ML services, such as Azure Machine Learning workspaces, Azure AI services, and Graphics Processing Units (GPU)-enabled virtual machines.
• Monitor and optimize the performance, capacity, and cost-effectiveness of AI infrastructure, ensuring efficient utilization of compute and storage resources for AI/ML models.
• Collaborate with data scientists and AI/ML engineers to support the deployment and operationalization of AI models within the cloud environment.
• Provide after-hours support for emergencies and occasional weekend maintenance.
• Develop and maintain current operational procedures, user documentation, and user training materials applicable to the supported systems.

Requirements

• Bachelor's degree in engineering/science/information technology discipline with a minimum of 4 years of relevant experience (6 to 10 years typical).
• OR Master's degree in engineering/science/information technology discipline with a minimum of 2 years of relevant experience.
• OR PhD.
• OR applicants without a bachelor's degree may be considered based on a combination of at least 12 years of completed education and/or relevant experience.
• Requires a Department of Energy (DOE) Q clearance; ability to obtain and maintain this clearance is required.
• U.S. citizenship is required for security clearance applicants.
• Position may require entry into Materials Access Areas (MAA) and participation in the Human Reliability Program (HRP). If HRP is required, candidate must complete a counterintelligence-scope polygraph, pursuant to 10 Code of Federal Regulations (CFR) 709. Medical requirements may apply.

Preferred Qualifications

• System administration skills in server operating systems such as Microsoft Windows or Linux.
• In-depth problem-solving and troubleshooting abilities.
• Clear communication (oral and written) with technical and non-technical staff.
• 3+ years of cloud administration in either Azure or AWS environment.
• 3+ years working with Infrastructure as a Service (IaaS), SaaS, or PaaS environments hosted in either Azure or AWS.
• Familiarity with Azure's AI and Machine Learning services and their underlying infrastructure.
• Understanding of compute requirements for AI/ML workloads, including GPU provisioning and configuration.
• Bachelor's degree in engineering/science/information technology discipline with a minimum of five years of relevant experience or a Master's degree with a minimum of three years of relevant experience.
• Experience with FedRAMP cloud requirements and GovCloud Environments.
• General understanding of Networking equipment and technology.
• Experience with backup/recovery and disaster recovery in a cloud environment.
• Experience with implementing cybersecurity controls and monitoring in a cloud environment.
• Strong scripting skills (e.g., PowerShell, Azure CLI, Python, Bash, IaC).
• Experience with Hypervisor technologies such as VMWare or Hyper-V.
• Experience with SAML authentication and identity federation in cloud environments (AWS, Azure).
• Experience with multi-factor authentication in cloud environments (AWS, Azure).
• Experience with Azure Cost Management or AWS Cost Explorer.
• Hands-on experience deploying and managing AI/ML-specific Azure services (e.g., Azure Machine Learning, Azure Cognitive Services, Azure Databricks).
• Knowledge of Machine Learning Operations (MLOps) principles and practices, particularly as they relate to infrastructure automation and monitoring.
• Experience with containerization technologies (e.g., Docker, Kubernetes) for deploying AI applications.

Benefits

At Pantex, you’ll discover a career of purpose with a benefits package designed for your total peace of mind, including:

• Comprehensive health coverage.
• Robust retirement planning.
• Opportunities for continuous learning through education reimbursement.
• Flexibility to support a balanced life.

Pantex is a drug-free workplace. Candidates accepting a job offer will be required to pass a pre-placement physical, drug screening, and background investigation. All employees are subject to random selection for drug testing without advance notification.