Site Reliability Engineer | AWS

XDI Solutions is seeking an experienced Site Reliability Engineer to support secure, scalable, and highly available cloud infrastructure. The role focuses on AWS infrastructure management, automation, reliability engineering, CI/CD, observability, troubleshooting, security, and operational resilience across complex enterprise environments.

Responsibilities:

• Build, manage and optimize AWS cloud infrastructure across production environments
• Improve platform reliability, availability, scalability and performance
• Automate infrastructure provisioning and configuration using Infrastructure as Code
• Build and maintain CI/CD pipelines and deployment automation
• Implement monitoring, logging, alerting and observability across applications and infrastructure
• Troubleshoot complex production, infrastructure and networking issues
• Support incident response, root-cause analysis and preventative engineering
• Implement cloud security, IAM, networking and infrastructure best practices
• Work closely with software, platform, security and DevOps teams to improve engineering standards and operational resilience

Requirements:

• MUST BE US CITIZEN
• Strong experience in Site Reliability Engineering, DevOps, Platform Engineering or Cloud Infrastructure
• Deep hands-on experience with AWS
• Strong knowledge of Linux, networking, DNS, load balancing and cloud security
• Experience with Terraform, CloudFormation or similar Infrastructure-as-Code tooling
• Experience with Docker and Kubernetes/EKS
• Strong scripting/automation skills using Python, Bash or similar
• Experience with CI/CD tooling such as GitHub Actions, GitLab CI, Jenkins or equivalent
• Knowledge of monitoring and observability platforms such as CloudWatch, Datadog, Prometheus or Grafana
• Understanding of DevSecOps, IAM and security best practices
• Strong troubleshooting skills within complex, distributed environments
• Experience supporting enterprise, manufacturing or industrial environments
• AWS certifications
• Experience with cloud-native application architectures
• Exposure to infrastructure supporting AI/ML workloads or data platforms