> Markdown version of [/jobs/ext/4571112-aws-devops-engineer-ai-ml-mlops](https://www.wearedevelopers.com/jobs/ext/4571112-aws-devops-engineer-ai-ml-mlops). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# AWS DevOps Engineer AI/ML & MLOps

- **Company:** eTeam Inc
- **Location:** Tampa, FL, United States
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Cloud Engineering, Configuration Management, System Configuration, Continuous Integration, DevOps, Github, Identity and Access Management, Key Management, Machine Learning, Performance Tuning, Software Tools, OpenAI, Prometheus, Azure Machine Learning, Software Deployment, Data Logging, LangChain, Retrieval-Augmented Generation, Delivery Pipeline, Large Language Models, Grafana, Kubernetes Helm Charts, Generative AI, Infrastructure as Code (IaC), Agentic-AI, Containerization, Gitlab-ci, Git Flow, Kubernetes, Amazon Bedrock, HuggingFace, Machine Learning Operations, Cloudwatch, Terraform, Software Version Control, Devsecops, Docker, Elk Stack, Jenkins, Vulnerability Analysis
- **Published:** November 4, 2026
- **Apply:** https://www.thejobnetwork.com/job/46004ded-6d08-4fb1-8c85-5e83450f3efe/aws-devops-engineer-aiml-mlops

## About the Role

* Generative AI deployment experience using Amazon Bedrock, OpenAI, Anthropic, or Hugging Face models.
 * Experience with LLM deployment, vector databases, and RAG architectures.
 * Knowledge of LangChain, AI Agents, and AI workflow automation.
 * Exposure to Data Engineering tools such as Glue, Athena, EMR, or Redshift.
 * Experience implementing AI governance and model security frameworks.

## Description

We are looking for an experienced AWS DevOps Engineer with strong expertise in Terraform, CI/CD automation, and AI/ML platform deployment. The ideal candidate will be responsible for building, automating, and managing scalable cloud infrastructure on AWS while enabling AI/ML workloads through robust DevOps practices. This role requires hands-on experience in Infrastructure as Code (IaC), containerization, cloud-native technologies, MLOps, and automation., Cloud Infrastructure & Automation

 * Design, deploy, and manage highly available and secure AWS cloud environments.
 * Develop and maintain Infrastructure as Code (IaC) using Terraform.
 * Automate cloud provisioning, configuration management, and environment setup.
 * Implement cloud governance, security, compliance, and cost optimization strategies.

DevOps & CI/CD

 * Design and manage CI/CD pipelines using GitHub Actions, Jenkins, GitLab CI/CD, or AWS CodePipeline.
 * Automate application deployments across development, testing, and production environments.
 * Implement GitOps and DevSecOps best practices.
 * Manage source control repositories and branching strategies.

AI/ML & MLOps

 * Deploy, automate, and manage AI/ML solutions on AWS.
 * Support ML lifecycle management, including model training, validation, deployment, and monitoring.
 * Work with Amazon SageMaker for model development and deployment.
 * Implement MLOps pipelines for continuous model integration and delivery.
 * Collaborate with Data Scientists and AI Engineers to operationalize machine learning models.

Containerization & Orchestration

 * Build and manage containerized workloads using Docker.
 * Deploy and manage Kubernetes clusters using Amazon EKS.
 * Implement Helm charts and Kubernetes best practices for scalable deployments.
 * Monitoring & Security
 * Configure monitoring, logging, and alerting using CloudWatch, Prometheus, Grafana, and ELK Stack.
 * Implement IAM policies, security controls, secrets management, and vulnerability scanning.
 * Monitor infrastructure health and optimize system performance.