AI Cloud Engineer

Senior AI Cloud Engineer (Hybrid - North Carolina) A rapidly growing enterprise technology organization is seeking a Senior AI Cloud Engineer to help build and scale next-generation AI and cloud solutions in a highly regulated environment. This role will focus on deploying enterprise-grade GenAI capabilities, improving cloud infrastructure, and enabling AI adoption across the business through scalable engineering practices. This is an opportunity to join a newly expanding AI and platform engineering team responsible for operationalizing AI initiatives at scale while partnering closely with engineering, data, product, and infrastructure teams. Responsibilities Design, deploy, and maintain scalable AI and cloud infrastructure solutions in AWS Build and support enterprise GenAI platforms and reusable AI engineering frameworks Develop and manage CI/CD pipelines for AI and cloud services Automate infrastructure provisioning using Infrastructure as Code (Terraform preferred) Collaborate with cross-functional teams to integrate AI capabilities into enterprise applications and workflows Implement monitoring, observability, governance, and cost optimization practices across AI systems Support containerized deployments and cloud-native application architectures Troubleshoot production issues across infrastructure, applications, and AI/model services Contribute to best practices around security, automation, resiliency, and cloud operations Required Qualifications Bachelor's degree in Computer Science, Information Systems, Engineering, or related field 5+ years of experience building and supporting AWS cloud environments Strong experience with AWS services such as ECS/ECR, Lambda, API Gateway, S3, RDS/Aurora, DynamoDB, IAM, VPC, CloudWatch, and related services Hands‑on experience with CI/CD pipelines using GitHub Actions, GitLab, Jenkins, or similar tools Experience with Infrastructure as Code using Terraform or equivalent tooling Strong scripting/programming skills in Python and Bash Experience with Docker and containerized deployments Strong understanding of cloud security, governance, monitoring, and operational best practices Ability to work collaboratively in fast‑paced, cross‑functional environments Preferred Experience Experience supporting or deploying GenAI/LLM platforms Exposure to AWS Bedrock, OpenAI, Azure AI Services, or similar AI ecosystems Experience working within highly regulated enterprise environments Familiarity with AI governance, model life‑cycle management, and operational monitoring Understanding of secure application design and modern DevOps practices Additional Information Hybrid work environment based in North Carolina Strong emphasis on innovation, collaboration, and scalable engineering Opportunity to help shape AI platform strategy and enterprise AI adoption Competitive compensation package and long‑term growth potential #J-18808-Ljbffr