Cloud Engineer

Kellton is seeking a Senior Cloud Engineer for a client, primarily focusing on AWS solutions and infrastructure development. The role involves designing and deploying scalable AI solutions, integrating cloud operations, and collaborating with security and application teams to ensure responsible AI usage.

Responsibilities:

• 3 years AWS experience
• 3-5 years’ experience developing infrastructure and platform pipelines for agile delivery to application teams
• AWS Certifications highly desired
• AI first mentality to improving processes
• Led design and production deployment of AWS GenAI solutions using Amazon Bedrock, enabling scalable, low-latency AI inference without managing model infrastructure or GPUs
• Established enterprise AI platform patterns, balancing performance, cost, and safety through managed inference, prompt governance, and observability
• Integrated Amazon Q/Kiro into cloud operations to accelerate troubleshooting, architecture analysis, and root-cause investigation using AWS context-aware AI
• Partnered with security and application teams to operationalize responsible AI usage aligned with enterprise standards
• Experience with AWS, VPC, AZs, Subnets, Route53, ALB/NLB, WAF, Stacksets, Security Groups, NACLs, EC2, Systems Manager, Azure Devops, Ansible, Jenkins
• Strong knowledge of Windows and Linux operating systems. RHEL 8.x-9.x, SUSE and Windows Server 2019 and greater
• Fundamental networking/distributed computing environment concepts (Routing protocols, DHCP, DNS, TCP/IP)
• Excellent understanding of Containers, including AWS technologies ECR, EMR, EKS
• Understanding of Monitoring tools like Cribl, CloudWatch and Zabbix
• Troubleshooting software and hardware issues including root cause analysis
• Strong developer mindset with experience developing in CloudFormation, Terraform, Python, YAML, JSON
• Strong platform engineering background automating provisioning of resources in AWS

Requirements:

• 3 years AWS experience
• 3-5 years' experience developing infrastructure and platform pipelines for agile delivery to application teams
• AWS Certifications highly desired
• AI first mentality to improving processes
• Led design and production deployment of AWS GenAI solutions using Amazon Bedrock, enabling scalable, low-latency AI inference without managing model infrastructure or GPUs
• Established enterprise AI platform patterns, balancing performance, cost, and safety through managed inference, prompt governance, and observability
• Integrated Amazon Q/Kiro into cloud operations to accelerate troubleshooting, architecture analysis, and root-cause investigation using AWS context-aware AI
• Partnered with security and application teams to operationalize responsible AI usage aligned with enterprise standards
• Experience with AWS, VPC, AZs, Subnets, Route53, ALB/NLB, WAF, Stacksets, Security Groups, NACLs, EC2, Systems Manager, Azure Devops, Ansible, Jenkins
• Strong knowledge of Windows and Linux operating systems. RHEL 8.x-9.x, SUSE and Windows Server 2019 and greater
• Fundamental networking/distributed computing environment concepts (Routing protocols, DHCP, DNS, TCP/IP)
• Excellent understanding of Containers, including AWS technologies ECR, EMR, EKS
• Understanding of Monitoring tools like Cribl, CloudWatch and Zabbix
• Troubleshooting software and hardware issues including root cause analysis
• Strong developer mindset with experience developing in CloudFormation, Terraform, Python, YAML, JSON
• Strong platform engineering background automating provisioning of resources in AWS
• Bachelor's degree in computer science, or combination of education and experience
• AWS certification highly preferred