Mid Cloud Engineer

Strategic ACI; Washington (District of Columbia); On-site; USD 150,000 - 190,000; Full time

Job summary

Strategic ACI seeks a seasoned Cloud Infrastructure Engineer to design, implement, and optimize secure cloud environments for testing and evaluation of AI/ML models. You will work with software, platform, and DevSecOps teams to provision GPU-enabled resources and automate infrastructure as code to support scalable T&E-as-a-Service.

Your responsibilities include building architectures for parallel model evaluation, managing artifacts, and ensuring performance, reliability, and cost efficiency.

Qualifications

• Bachelor's degree in a STEM field or equivalent experience.
• 5+ years of experience developing or supporting cloud-based software/infrastructure solutions.
• Experience with AWS, Azure, or comparable cloud platforms.
• Experience provisioning and managing Linux-based compute environments.
• Familiarity with GPU-enabled computing environments for AI/ML workloads.
• Experience with Infrastructure as Code tools (Terraform, CloudFormation, Ansible).
• Experience automating with Python, Bash, PowerShell, or similar scripting languages.
• Experience using Git and modern software development practices.

Responsibilities

• Collaborate with software, platform, and DevSecOps engineers to design, build, and deploy secure cloud-based T&E environments.
• Provision, configure, and manage GPU-enabled compute resources supporting AI/ML model testing and evaluation.
• Develop and maintain automated cloud infrastructure for scalable T&E-as-a-Service capabilities.
• Design cloud architectures for parallel model evaluation, workload orchestration, and efficient resource usage.
• Implement centralized artifact management for AI/ML models, outputs, datasets, and packages.
• Optimize cloud infrastructure for performance, scalability, reliability, and cost across T&E workloads.
• Develop automation to accelerate deployment, execution, and monitoring of AI/ML evaluation pipelines.
• Collaborate with AI/ML Test Engineers, Data Scientists, CV Scientists, and Platform Engineers to integrate cloud services into enterprise T&E workflows.
• Monitor cloud resources, troubleshoot infrastructure issues, and implement performance improvements for mission operations.
• Produce technical documentation covering cloud architecture, automation, deployment procedures, and best practices.

Education

Bachelor's degree in Computer Science, Software Engineering, Computer Engineering, Information Systems, or a related STEM field

Tools

Terraform

AWS CloudFormation

Ansible

Kubernetes

Docker

Git

Job description

Responsibilities:

• Collaborate with software, platform, and DevSecOps engineers to design, build, and deploy secure cloud-based T&E environments.
• Provision, configure, and manage GPU-enabled compute resources supporting AI/ML model testing and evaluation.
• Develop and maintain automated cloud infrastructure that enables scalable T&E-as-a-Service (T&EaaS) capabilities.
• Design cloud architectures supporting parallel model evaluation, workload orchestration, and efficient resource utilization.
• Implement centralized artifact management solutions supporting AI/ML models, evaluation outputs, datasets, and software packages.
• Optimize cloud infrastructure for performance, scalability, reliability, and cost efficiency across T&E workloads.
• Develop automation that accelerates deployment, execution, and monitoring of AI/ML evaluation pipelines.
• Collaborate with AI/ML Test Engineers, Data Scientists, Computer Vision Scientists, and Platform Engineers to integrate cloud services into enterprise T&E workflows.
• Monitor cloud resources, troubleshoot infrastructure issues, and implement performance improvements supporting mission operations.
• Produce technical documentation supporting cloud architecture, infrastructure automation, deployment procedures, and operational best practices.

Qualifications:

Required:

• Active TS/SCI clearance and the ability to pass a CI polygraph within 30 days.
• Bachelor's degree in Computer Science, Software Engineering, Computer Engineering, Information Systems, or a related STEM field (or additional relevant experience in lieu of a degree).
• 5+ years of experience developing or supporting cloud-based software or infrastructure solutions.
• Experience with AWS, Azure, or comparable cloud computing platforms.
• Experience provisioning and managing Linux-based compute environments.
• Familiarity with GPU-enabled computing environments supporting AI/ML workloads.
• Experience with Infrastructure as Code tools such as Terraform, AWS CloudFormation, or Ansible.
• Experience developing automation using Python, Bash, PowerShell, or similar scripting languages.
• Experience using Git and modern software development practices.
• Strong analytical, troubleshooting, and problem-solving skills.
• Ability to work effectively within Agile and DevSecOps development teams.

Desired:

• Experience supporting DoD, NGA, or Intelligence Community programs.
• Experience supporting AI/ML operational environments, T&E infrastructure, or MLOps platforms.
• Experience with Kubernetes, Docker, container orchestration, and cloud-native application deployment.
• Familiarity with workload schedulers, distributed computing, or parallel processing environments.
• Experience supporting GPU clusters used for AI/ML model training, inference, or evaluation.
• Familiarity with secure cloud architectures, RMF, and Authority to Operate (ATO) requirements.
• Experience supporting GEOINT systems or enterprise AI/ML evaluation environments.