Lead Consultant | Cloud Platform | Amazon Webservices DevOps

Job-ID29005645Reference26-07967Description: POC: Bharath Subramanya******ATTENTION ALL SUPPLIERS******READ BEFORE SUBMITTING:• UPDATED CONTACT NUMBER and EMAIL ID is a MANDATORY REQUEST from our client for all the submissions• Limited to 2 submission per supplier. Please submit your best.• We prioritize endorsing those with complete and accurate information• Avoid submitting duplicate profiles. We will Reject/Disqualify immediately.• Make sure that candidate's interview schedules are updated. Please inform the candidate to keep their lines open.MANDATORY: Please include in the resume the candidate’s complete & updated contact information (Phone number, Email address and Skype ID) as well as a set of 5 interview timeslots over a 72-hour period after submitting the profile when the hiring managers could potentially reach to them. PROFILES WITHOUT THE REQUIRED DETAILS and TIME SLOTS will be REJECTED.Job title: AWS + Terraform with AIWork Location: Tampa, FLVendor Rate: ***/hrMinimum years of experience: 8+ YrsWould you require the candidates to meet you for in person interview? NoIs Skype/WebEx interview,OK? OKIs this onsite/remote position: HybridIf onsite, will you be considering relocation candidates: NoDoes this position require Visa independent candidates only? YesJob 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 ResponsibilitiesCloud Infrastructure & AutomationDesign, 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/CDDesign 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 & MLOpsDeploy, 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 & OrchestrationBuild 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 & SecurityConfigure 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-HaveGenerative 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.Custom Fields: Name: Intake Call RequestedValue: trueName: Intake Call CompletedValue: true