Devops engineer with AI

Sage IT Inc
Alpharetta, GA, United States
11 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
9 years minimum
Working hours
Regular working hours
Job source

Tech stack

Agile Methodology Artificial Intelligence Amazon Web Services Amazon Elastic Compute Cloud Amazon S3 Cloud Engineering Continuous Integration Information Engineering DevOps Github Monitoring of Systems Identity and Access Management
+31 more
Key Management Machine Learning Release Management Cloud Services Prometheus Data Logging Cloud Platform System Retrieval-Augmented Generation Delivery Pipeline Grafana Generative AI Infrastructure as Code (IaC) Amazon Virtual Private Cloud (VPC) Agentic-AI Git Cloudformation Containerization AI Platforms Kubernetes Infrastructure Automation Frameworks Amazon Bedrock Machine Learning Operations Functional Programming Cloudwatch Model Context Protocol Terraform Splunk Devsecops Docker Jenkins Servicenow

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., 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

Requirements

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

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