Cloud Engineer

Target salary range: $100k - $125k. The estimate displayed represents the typical salary range for this position based on experience and other factors.

• Bachelor’s degree in Computer Science, Information Systems, or related technical discipline.
• 3+ years of experience in cloud engineering, infrastructure engineering, or DevOps roles.
• Experience designing and deploying solutions in Microsoft Azure.
• Experience implementing Infrastructure as Code and automated deployment pipelines.
• Familiarity with containerization technologies such as Docker or Kubernetes.
• Knowledge of secure cloud architecture and cybersecurity best practices.
• Experience working in Agile development environments.
• Active Security clearance required.
• Microsoft Azure / Azure Government.
• Infrastructure as Code (Terraform, ARM, Bicep).
• Kubernetes and container platforms.
• CI/CD tools (GitLab, GitHub, Azure DevOps).
• Python or PowerShell automation.
• Monitoring and observability platforms such as Azure Monitor, Prometheus, and Grafana.
• Identity and access management using Azure Active Directory.

• Microsoft Azure certifications (AZ-104, AZ-305, or similar).
• Experience working in Azure Government or other DoD cloud environments.
• Familiarity with DoD cybersecurity frameworks such as RMF and STIG implementation.
• Experience supporting enterprise data platforms, analytics environments, or AI/ML workloads.

This engineer turns mission intent into cloud reality. In Azure and Azure Government, they automate everything—from infrastructure and security baselines to CI/CD pipelines—so analytic teams can deploy models quickly and safely. The Cloud Engineer’s work hardens container platforms, elevates reliability and observability, and embeds compliance into the platform itself, enabling the Army’s Data Science Environment to scale without sacrificing trust.

• →Building and improving the secure cloud platform that powers the Army’s Data Science Environment (DSE).
• →Enabling data scientists and analytic teams to rapidly deploy AI/ML models and advanced analytics tools.
• →Automating cloud infrastructure and platform services using modern DevSecOps and Infrastructure as Code practices.
• →Improving reliability, scalability, and observability of enterprise data and analytics platforms.
• →Supporting containerized analytic workloads used by multiple Army organizations
• →Designing secure architectures and automated compliance capabilities within DoD cloud environments.
• →Helping analytic teams move faster by providing stable, automated, and secure platform services.
• →Design, deploy, and maintain cloud infrastructure in Microsoft Azure and Azure Government environments.
• →Develop and manage Infrastructure as Code (IaC) using tools such as Terraform, ARM templates, or Bicep.
• →Build and support CI/CD pipelines for automated infrastructure and application deployments.
• →Deploy and manage containerized workloads using Docker and Kubernetes.
• →Implement DevSecOps practices integrating security scanning, compliance validation, and automated testing.
• →Configure monitoring, logging, and observability solutions to ensure system performance and reliability.
• →Implement cloud security controls including RBAC, secure configuration baselines, and STIG compliance.
• →Collaborate with software developers, data engineers, data scientists, and cybersecurity teams to support modern cloud platforms.
• →Document technical solutions, architecture decisions, and operational procedures.
• →Support operational reliability, incident response, and platform performance tuning.