Lead Consultant | Cloud Platform | Amazon Webservices DevOps

Description: POC: Bharath Subramanya

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Job title: AWS + Terraform with AI

Work Location: Tampa, FL

Vendor Rate: ***/hr

Minimum years of experience: 8+ Yrs

Would you require the candidates to meet you for in person interview? No

Is Skype/WebEx interview,OK? OK

Is this onsite/remote position: Hybrid

If onsite, will you be considering relocation candidates: No

Does this position require Visa independent candidates only? Yes

Job 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.

Key Responsibilities

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.

Nice-to-Have

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.

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Name: Intake Call Completed

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