About the role
Overview We are seeking a highly skilled AWS DevOps Engineer with Generative AI experience to serve as a subject matter expert (SME) for our AWS cloud environment. This role requires deep hands-on expertise in AWS infrastructure, Infrastructure as Code (Terraform), DevOps automation, Python scripting, and AI/GenAI solutions within the AWS ecosystem. The ideal candidate will have strong experience designing, deploying, securing, and supporting cloud-native solutions while also contributing to AI initiatives leveraging AWS Bedrock, AgentCore, and related services. Key Responsibilities Design, implement, and maintain scalable, secure, and highly available AWS cloud infrastructure. Develop and manage Infrastructure as Code (IaC) using Terraform. Build and optimize CI/CD pipelines for automated deployments and infrastructure provisioning. Automate operational processes using Python and cloud-native tools. Monitor, troubleshoot, and resolve complex AWS infrastructure and application issues. Serve as the AWS SME for architecture reviews, cloud governance, security, and best practices. Design and support Generative AI solutions using AWS Bedrock and related AWS AI services. Implement AI governance, security controls, guardrails, and responsible AI practices. Collaborate with development, security, and data teams to deploy AI-powered applications. Drive cloud optimization, performance tuning, and cost management initiatives. Required Qualifications 7+ years of experience in DevOps, Cloud Engineering, or Site Reliability Engineering. 5+ years of hands-on AWS experience in enterprise environments. Expert-level knowledge of AWS services including: EC2, VPC, IAM, Route 53 ECS, EKS, Lambda CloudWatch, CloudTrail S3, RDS, DynamoDB Security and Networking services Strong Terraform expertise with experience developing reusable modules and managing large-scale AWS infrastructure. Strong Python scripting and automation experience. Extensive experience with CI/CD tools such as Jenkins, GitHub Actions, GitLab CI, or AWS CodePipeline. Experience with Docker and Kubernetes. Strong troubleshooting and production support experience. AI / Generative AI Requirements Experience building, deploying, or supporting AI/GenAI solutions. Hands-on experience with: AWS Bedrock Bedrock Agents / AgentCore Foundation Models and Model Invocation Retrieval-Augmented Generation (RAG) Understanding of: AI hallucinations and mitigation strategies AI governance and security Model access controls and permissions Agent-based architectures Prompt engineering and guardrails Experience implementing secure and compliant AI solutions in enterprise environments. Preferred Qualifications AWS certifications (Solutions Architect, DevOps Engineer Professional, Security Specialty, etc.). Experience with SageMaker and MLOps pipelines. Knowledge of cloud security frameworks and compliance standards. Experience working in highly regulated environments such as banking, healthcare, or insurance. What We're Looking For Deep AWS expertise with strong hands-on troubleshooting capabilities. Advanced Terraform proficiency. Strong Python automation skills. Proven experience with AWS-based AI/Generative AI solutions. Ability to operate as a trusted AWS and AI SME across the organization.
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About the role
Overview We are seeking a highly skilled AWS DevOps Engineer with Generative AI experience to serve as a subject matter expert (SME) for our AWS cloud environment. This role requires deep hands-on expertise in AWS infrastructure, Infrastructure as Code (Terraform), DevOps automation, Python scripting, and AI/GenAI solutions within the AWS ecosystem. The ideal candidate will have strong experience designing, deploying, securing, and supporting cloud-native solutions while also contributing to AI initiatives leveraging AWS Bedrock, AgentCore, and related services. Key Responsibilities Design, implement, and maintain scalable, secure, and highly available AWS cloud infrastructure. Develop and manage Infrastructure as Code (IaC) using Terraform. Build and optimize CI/CD pipelines for automated deployments and infrastructure provisioning. Automate operational processes using Python and cloud-native tools. Monitor, troubleshoot, and resolve complex AWS infrastructure and application issues. Serve as the AWS SME for architecture reviews, cloud governance, security, and best practices. Design and support Generative AI solutions using AWS Bedrock and related AWS AI services. Implement AI governance, security controls, guardrails, and responsible AI practices. Collaborate with development, security, and data teams to deploy AI-powered applications. Drive cloud optimization, performance tuning, and cost management initiatives. Required Qualifications 7+ years of experience in DevOps, Cloud Engineering, or Site Reliability Engineering. 5+ years of hands-on AWS experience in enterprise environments. Expert-level knowledge of AWS services including: EC2, VPC, IAM, Route 53 ECS, EKS, Lambda CloudWatch, CloudTrail S3, RDS, DynamoDB Security and Networking services Strong Terraform expertise with experience developing reusable modules and managing large-scale AWS infrastructure. Strong Python scripting and automation experience. Extensive experience with CI/CD tools such as Jenkins, GitHub Actions, GitLab CI, or AWS CodePipeline. Experience with Docker and Kubernetes. Strong troubleshooting and production support experience. AI / Generative AI Requirements Experience building, deploying, or supporting AI/GenAI solutions. Hands-on experience with: AWS Bedrock Bedrock Agents / AgentCore Foundation Models and Model Invocation Retrieval-Augmented Generation (RAG) Understanding of: AI hallucinations and mitigation strategies AI governance and security Model access controls and permissions Agent-based architectures Prompt engineering and guardrails Experience implementing secure and compliant AI solutions in enterprise environments. Preferred Qualifications AWS certifications (Solutions Architect, DevOps Engineer Professional, Security Specialty, etc.). Experience with SageMaker and MLOps pipelines. Knowledge of cloud security frameworks and compliance standards. Experience working in highly regulated environments such as banking, healthcare, or insurance. What We're Looking For Deep AWS expertise with strong hands-on troubleshooting capabilities. Advanced Terraform proficiency. Strong Python automation skills. Proven experience with AWS-based AI/Generative AI solutions. Ability to operate as a trusted AWS and AI SME across the organization.