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Devops engineer with AI

Sage IT IncGA🇺🇸United States

Quick overview

SeniorityMid Senior
Work modeOn Site
LocationGA, United States
DockerGitAWSMLOpsSplunkCloudFormationGitHub ActionsGrafanaHelmJenkinsPrometheusPythonTerraformGenerative AIKubernetesAgileCI/CDRAGIAM

Job description

AWS DevOps Engineer with AI/ML Experience

Location: Alpharetta, GA (Onsite)

Job Type: Full-Time

Job Description

We are seeking an experienced AWS DevOps Engineer with AI/ML expertise to join our team in Alpharetta, GA. The ideal candidate will be responsible for designing, implementing, and managing cloud-native infrastructure, CI/CD pipelines, containerized applications, and AI/ML deployment platforms in AWS.

Required Skills

9+ years of experience in DevOps, Cloud Engineering, or Platform Engineering

Strong hands-on experience with AWS Cloud Services (EC2, EKS, ECS, Lambda, S3, IAM, VPC, CloudWatch)

Expertise in Terraform, CloudFormation, and Infrastructure as Code (IaC)

Experience with Docker, Kubernetes (EKS), Helm

Strong experience in CI/CD tools such as Jenkins, GitHub Actions, AWS CodePipeline, and CodeBuild

Proficiency in Python scripting and automation

Experience supporting AI/ML workloads using Amazon SageMaker, Amazon Bedrock, or similar AI platforms

Knowledge of MLOps/LLMOps concepts, model deployment, monitoring, and automation

Experience with monitoring tools such as CloudWatch, Prometheus, Grafana, and Splunk

Strong understanding of security best practices, IAM, Secrets Management, and DevSecOps

Experience with Git, Agile methodologies, and release management

Preferred Skills

Experience with Generative AI, RAG, Vector Databases, and AI Agents

Knowledge of MCP (Model Context Protocol)

Experience with ServiceNow integrations

AWS Certifications preferred

Responsibilities

Design and implement scalable AWS cloud infrastructure

Develop and maintain CI/CD pipelines for cloud and AI/ML applications

Deploy and manage containerized applications on Kubernetes/EKS

Automate infrastructure provisioning using Terraform and CloudFormation

Support MLOps/LLMOps pipelines for AI model deployment and monitoring

Implement observability, logging, and monitoring solutions

Collaborate with development, data engineering, and AI teams to deliver reliable cloud solutions

Ensure security, compliance, and operational excellence across environments

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