Summary
✨ AI‑Generated
A DevOps engineer will design and operate scalable AWS infrastructure using infrastructure as code, build Kubernetes environments, automate deployments, monitor cloud systems, and develop CI/CD practices. The role also includes troubleshooting cloud-native environments, contributing to architecture decisions, and exploring AI-assisted automation for infrastructure and security workflows.
Highlights
Work extensively with AWS, Kubernetes, Terraform, CI/CD, and cloud-native automation while contributing to architecture decisions and emerging AI-assisted infrastructure workflows.
Description
Key Responsibilities:
· Design, deploy, and manage scalable cloud infrastructure on AWS using Terraform (Infrastructure as Code).
· Build and maintain Kubernetes clusters on AWS using EKS.
· Automate provisioning, configuration management, and application deployments.
· Monitor cloud infrastructure health and performance, and implement improvements as needed.
· Collaborate with DevOps, development, and security teams to build CI/CD pipelines and enforce best practices.
· Provide operational support and troubleshooting of cloud-native environments.
· Contribute to architecture and design decisions around cloud and container orchestration.
· Maintain documentation related to system configuration, standards, and best practices.
· Assist with occasional projects or deployments in Microsoft Azure environments.
· Build and maintain AI-assisted automation for infrastructure and pipeline tasks (e.g., AI-driven IaC generation, automated code/security review).
Requirements:
· 5+ years of professional experience in cloud engineering or DevOps roles.
· Proven expertise in AWS services including EC2, VPC, IAM, S3, CloudWatch, and especially EKS.
· Strong experience in Terraform for managing infrastructure as code.
· Familiarity with CI/CD pipelines, scripting (e.g., Bash, Python), and configuration management tools.
· Working knowledge of Azure cloud fundamentals and services.
· Experience with Docker, Kubernetes, and container orchestration.
· Solid understanding of networking, security best practices, and cost optimization in cloud environments.
· Excellent problem-solving skills and ability to work independently or in a team.
· Experience integrating AI/LLM tooling into DevOps workflows (e.g., MCP servers, AI-assisted pipelines).
Preferred Qualifications:
· Certifications such as AWS Certified Solutions Architect, Certified Kubernetes Administrator (CKA), or Microsoft Azure Fundamentals.
· Experience with monitoring/logging tools like Prometheus, Grafana, ELK stack, or Cloud-native alternatives.
· Exposure to GitOps tools (e.g., ArgoCD, Flux) is a plus.
· Familiarity with other IAC tools like CloudFormation
· Exposure to Model Context Protocol (MCP) or similar AI-tool integration frameworks.
· Experience building AI-powered automation for code review, IaC generation, or config management.
