AWS DevOps (AI Engineer)

About the Role

Seeking a hands-on AWS DevOps Engineer to build, secure, automate, and operate production-grade AWS platforms supporting AI, GenAI, and Agentic AI solutions. This role is focused on engineering and delivery, enabling AI workloads to move from POC to scalable, secure, observable, and production-ready deployments.

Key Responsibilities

• Build and manage DEV, TEST, and PROD AWS environments for AI and Agentic AI workloads.
• Containerize and deploy applications using Docker, Kubernetes (EKS/ECS), and Amazon Bedrock AgentCore.
• Develop Infrastructure as Code (IaC) using Terraform, including networking, IAM, KMS, secrets management, and secure connectivity.
• Build and maintain secure DevSecOps CI/CD pipelines covering testing, security scanning, deployment, promotion, and rollback.
• Integrate AI evaluation, regression, and guardrail controls into deployment pipelines.
• Implement observability and monitoring using OpenTelemetry, ADOT, CloudWatch, and Bedrock AgentCore capabilities.
• Establish SRE practices including SLOs, resilience, incident management, root cause analysis, and production readiness.
• Optimize platform performance, scalability, reliability, and cloud costs using FinOps principles.
• Collaborate with AI Engineering, Security, Architecture, and Operations teams to establish reusable platform patterns and best practices.

Requirements & Tech Stack

• Strong hands-on experience in AWS DevOps, Platform Engineering, or Cloud Engineering roles.
• Proven experience building and operating production AWS environments and containerized workloads.
• Strong experience with Amazon Bedrock and Bedrock AgentCore.
• Expertise in Docker, Kubernetes/EKS, Terraform, and Infrastructure as Code.
• Strong CI/CD automation, DevSecOps, AWS security, IAM, and secrets management experience.
• Experience with OpenTelemetry, ADOT, CloudWatch, monitoring, logging, and distributed tracing.
• Strong understanding of SRE practices, including SLOs, resilience engineering, incident management, and RCA.
• Experience with Bash and/or Python automation.
• Practical experience with AWS cost optimization and FinOps practices.
• Strong collaboration, problem-solving, and platform consulting skills.

Mandatory Experience

• Proven experience building, automating, securing, deploying, and supporting production-grade AWS platforms and containerized workloads end-to-end.
• Hands-on experience with Amazon Bedrock and Bedrock AgentCore is essential.
• Production experience supporting AI, GenAI, or Agentic AI workloads is strongly preferred.
• Infrastructure support or CI/CD-only experience without production ownership is not sufficient.

Preferred Skills

• AgentOps and AI operations.
• AWS Control Tower, AWS Organizations, and multi-account environments.
• Helm, Argo CD, and GitOps.
• Prometheus and Grafana.
• High Availability and Disaster Recovery solutions.
• MCP, tool, and API integration experience.
• Experience working with SAP environments.

Preferred Certifications

• AWS Certified DevOps Engineer – Professional.
• AWS Certified Solutions Architect – Professional.
• Kubernetes and Terraform certifications.