AI Cloud Engineer
About The Position
Accenture Federal Services is seeking an AI Cloud Engineer to join their team and support a client at Hill AFB in Utah. This role focuses on building and operating the cloud infrastructure essential for AI/ML platform capabilities. These capabilities include GPU-enabled Kubernetes, data lake and streaming analytics infrastructure, and model registry/serving environments, all designed to support mission AI/ML workloads. The engineer will collaborate with AI/ML architecture and data platform teams, translating platform requirements into secure cloud infrastructure that adheres to Zero Trust and AI risk management expectations within a defense environment. The ideal candidate will possess hands-on cloud engineering experience, with a background in containerized AI/ML infrastructure, and be comfortable working in a dynamic, mission-critical setting.
Requirements
- 4 years of cloud engineering or infrastructure experience
- Working knowledge of Kubernetes, including GPU-enabled node pools
- Familiarity with data lake and/or streaming analytics concepts
- Familiarity with Zero Trust Architecture principles (NIST 800-207)
- Working knowledge of Infrastructure as Code (Terraform, Ansible, or CloudFormation)
- Scripting proficiency in Python, Bash, or PowerShell
- Must have an active Secret level clearance; Top Secret preferred
Nice To Haves
- Bachelor's degree in Computer Science, Data Engineering, Engineering, or related technical field (relevant certifications considered in lieu of degree)
- Exposure to containerized AI/ML infrastructure (GPU-enabled Kubernetes, model serving) or a strong willingness to develop this expertise quickly
- Familiarity with model registry and model-serving tooling
- Familiarity with NIST AI Risk Management Framework (AI RMF) concepts
- Experience with data pipeline tools (Apache Kafka, Apache Airflow, Apache Spark)
- AWS or Azure AI/ML-focused certifications
- CompTIA Security+ (current) or equivalent security certification
Responsibilities
- Build and operate GPU-enabled Kubernetes infrastructure supporting AI/ML training and inference workloads
- Support data lake and streaming analytics infrastructure feeding AI/ML pipelines
- Support model registry and model-serving infrastructure for AI/ML platform capabilities
- Implement Infrastructure as Code for AI/ML infrastructure components (Terraform, Ansible)
- Implement cloud security controls aligned with Zero Trust Architecture (NIST 800-207) principles for AI/ML infrastructure
- Support compliance activities relevant to AI risk management (NIST AI RMF) and CMMC requirements as they apply to AI/ML infrastructure
- Support STIG compliance checks and vulnerability remediation on AI/ML platform components
- Monitor and troubleshoot GPU-enabled compute and data pipeline infrastructure
- Support CI/CD pipeline operations for AI/ML model deployment workflows
- Collaborate with data platform and AI/ML architecture teams on infrastructure requirements
- Operate within an Agile framework — participate in sprints, standups, and retrospectives
- Document infrastructure decisions, runbooks, and operational procedures
- Support cross-training and knowledge sharing with the broader Develop & Build team
Benefits
- Hands-on experience
- Certifications
- Industry training
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
Associate degree
