AWS DevOps Engineer - Terraform & AI/ML

Job Title: AWS DevOps Engineer Terraform & AI/ML

Location: Tampa, FL (Hybrid)



Experience: 8+ Years



Employment Type: Contract

Job Summary

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

Key Responsibilities

• Design, deploy, and manage secure, scalable, and highly available AWS cloud infrastructure.
• Build and maintain Infrastructure as Code (IaC) using Terraform .
• Develop 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 DevOps, GitOps, and DevSecOps best practices.
• Deploy and manage containerized applications using Docker and Amazon EKS (Kubernetes) .
• Build and support MLOps pipelines for model training, validation, deployment, and monitoring using Amazon SageMaker .
• Collaborate with Data Scientists and AI Engineers to operationalize machine learning models.
• Configure monitoring, logging, and alerting using CloudWatch, Prometheus, Grafana, and ELK Stack .
• Implement cloud security using IAM, KMS, Secrets Manager , and vulnerability management best practices.
• Optimize cloud infrastructure for performance, reliability, scalability, and cost efficiency.

Required Skills

• 8+ years of experience in AWS Cloud and DevOps engineering.
• Strong hands-on experience with Terraform and Infrastructure as Code (IaC).
• Expertise in AWS services such as EC2, VPC, IAM, S3, Lambda, CloudWatch, EKS, ECS, Route 53, ALB/NLB, RDS , and Secrets Manager .
• Experience with Docker and Kubernetes (Amazon EKS) .
• Hands-on experience with CI/CD tools including GitHub Actions, Jenkins, GitLab CI/CD, or AWS CodePipeline .
• Experience implementing GitOps and DevSecOps practices.
• Strong scripting skills in Python or Bash .
• Experience with monitoring and logging tools such as CloudWatch, Prometheus, Grafana, and ELK .
• Strong understanding of AWS networking, security, IAM policies, and cloud governance.

Preferred Skills

• Experience with Amazon SageMaker , MLOps, and ML model deployment.
• Hands-on experience with Amazon Bedrock , OpenAI, Anthropic, or Hugging Face.
• Experience building or deploying LLM-based applications , RAG architectures , AI Agents, or LangChain solutions.
• Familiarity with vector databases such as OpenSearch, Pinecone, FAISS, or ChromaDB .
• Exposure to AWS data services including Glue, Athena, EMR, and Redshift .
• Experience with AI governance, model security, and compliance frameworks.

Preferred Qualifications

• AWS Certifications (Solutions Architect, DevOps Engineer, or Machine Learning Specialty) are highly preferred.
• Strong communication, troubleshooting, and problem-solving skills.
• Experience working in Agile/Scrum environments.