Senior Cloud Engineer (AI)

Senior Cloud Engineer (AI)

Job Category: Information Technology

Time Type: Full time

Minimum Clearance Required to Start: None

Employee Type: Regular

Percentage of Travel Required: Up to 10%

Type of Travel: Local

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The Opportunity:

CACI is seeking a Senior Cloud Engineer to join our team of technical and functional experts supporting the U.S. Department of Homeland Security (DHS) Headquarters, Chief Technology Officer Directorate (CTOD), Artificial Intelligence and Emerging Technology (AI/ET) initiative. This team works with a federal workforce staff with technical expertise for the smooth functioning of high-visibility, department-wide AI initiatives including Generative Artificial Intelligence solutions.

 

Ideal candidates will possess a robust technical background with ability to directly setup, configure, and script cloud services and infrastructure as part of small, agile teams developing new cloud-based AI/GenAI applications.  Candidates should have a deep understanding and experience using all facets of the well architected framework for cloud infrastructure and services to deliver robust, scalable, and resilient cloud-based applications.  Candidates demonstrating significant expertise in developing cloud infrastructure and services to deploy Generative AI (GenAI) solutions such as Azure OpenAI are highly desirable. A strong passion for AI technologies and a proven track record in planning and executing early-stage cloud applications should be clearly highlighted in the resume.

 

This is a remote work eligible position.

Responsibilities:

Responsibilities include, but are not limited to:

• Design, engineer, operate and optimize cloud native services and infrastructure for applications hosted in the cloud environment based on the principles of well-architected frameworks (Azure and AWS)
• Configure, create, and maintain effective solutions to monitor the health and performance of cloud infrastructure components including robust alerting and dashboards
• Develop Infrastructure as Code (IaC) and DevSecOps solutions to improve development velocity, and to automate infrastructure provisioning
• Communicate and collaborate proactively with client and peer engineering and product management resources in a professional and effective manner.
• Implement RAG architectures and other AI focused system architectures.

Qualifications:

Required: 

• Ability to obtain DoD Security Clearance
• Ability to obtain Department of Homeland Security (DHS) Entry On Duty (EOD) - Active EOD preferred
• MA/MS and 12 years’ experience in a related field, or equivalent (equivalency includes BA/BS + 15 years applicable experience)
• Demonstrated ability to analyze technically complex problems and develop and implement reliable solutions in a cloud environment
• Deep expertise in building and operating high performance systems in Azure Cloud environment, expertise in AWS a plus.
• Expertise in multiple software and scripting languages for cloud engineering including, but not limited to: Terraform, Python, JavaScript, BASH, PowerShell, SQL, YAML, and JSON.
• Expertise with DevSecOps/CICD pipeline management to create and automate cloud infrastructure provisioning through Infrastructure as Code (ex. Terraform, etc.), and Azure DevOps.
• Experience with monitoring infrastructure performance using Azure Monitor, Log Analytics, and Application Insights to set up a robust alerts and dashboards to monitor infrastructure health and performance, ideally in an Azure OpenAI system.  
• Experience implementing AI/ML/GenAI capabilities desired including an understanding of Retrieval Augmented Generation (RAG) based architectures
• Experience working in Agile software development environments
• Ability to work proactively and communicate professionally in a cross-functional team and client environment

Desired: 

• Experience with Azure OpenAI and understanding of Microsoft Azure services for Generative AI/LLM infrastructure.
• Experience with operating Kubernetes platforms, and experience building and deploying Docker applications.
• Experience with deploying and integrating Open-Source AI models.
• Experience integrating  and working with AWS Bedrock APIs
• Technical certifications in Microsoft Azure or Cloud such as Azure Solution Architect, AWS Certified Developer Associate or Azure Developer Associate.  
• Experience