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AWS DevOps Engineer W2 POSITION

SVK Technology SolutionsMI🇺🇸United StatesPosted 15 Jul 2026

Quick Overview

Work Type
On Site
Level
Mid Senior

Job Description

Only our W2.

AWS DevOps Engineer

Location: Grand Rapids, Michigan. - NEED LOCALS

***Position is on-site (Monday-Thursday) ***

We are seeking an experienced Senior DevOps Engineer to design, implement, and maintain scalable, reliable, and secure cloud infrastructure solutions. The ideal candidate is proactive, detail-oriented, and highly skilled in Kubernetes, AWS, Infrastructure as Code, and modern CI/CD practices.

This role will partner closely with development, quality assurance, product, and infrastructure teams to improve deployment processes, system reliability, operational efficiency, and overall platform performance.

Key Responsibilities:

Kubernetes and Container Orchestration

  • Design, deploy, manage, and optimize Kubernetes clusters supporting scalable and highly available workloads.
  • Implement container orchestration standards, security controls, resource management, and deployment best practices.
  • Integrate Kubernetes environments with automated build, testing, and deployment pipelines.
  • Troubleshoot cluster, application, networking, and performance-related issues.

AWS Cloud Infrastructure

  • Architect, implement, and manage cloud infrastructure using AWS services, including EC2, S3, VPC, RDS, Lambda, IAM, CloudWatch, and related technologies.
  • Design cloud-native solutions focused on scalability, availability, security, cost efficiency, and operational resilience.
  • Use AWS CDK and Terraform to automate infrastructure provisioning and configuration.
  • Maintain consistent infrastructure standards across development, testing, and production environments.

CI/CD and Automation

  • Develop and maintain CI/CD pipelines using AWS CodePipeline, Jenkins, or similar tools.
  • Automate build, testing, deployment, and infrastructure management processes.
  • Monitor and troubleshoot pipeline failures, performance issues, and deployment risks.
  • Develop automation and operational tooling using Python, Bash, or similar scripting languages.

Monitoring, Reliability, and Optimization

  • Implement and maintain monitoring, alerting, logging, and incident-management solutions using Prometheus, Grafana, Dynatrace, CloudWatch, or similar platforms.
  • Improve system performance, scalability, availability, and fault tolerance.
  • Participate in incident response, root-cause analysis, and the implementation of preventive actions.
  • Identify opportunities to improve infrastructure costs, operational processes, and system reliability.

AI-Enabled Engineering

  • Use Claude and other approved AI tools to accelerate troubleshooting, scripting, documentation, infrastructure design, and operational analysis.
  • Apply AI responsibly to enhance technical capabilities, improve delivery efficiency, and increase the quality and consistency of engineering work.

Required Skills and Experience:

  • Strong hands-on experience with Kubernetes administration, deployment, and container orchestration.
  • In-depth knowledge of AWS services, cloud infrastructure, and cloud-native architecture.
  • Experience with Infrastructure as Code using AWS CDK and Terraform.
  • Strong experience developing and maintaining CI/CD pipelines using AWS CodePipeline, Jenkins, or comparable platforms.
  • Working knowledge of Apache Kafka or similar distributed messaging technologies.
  • Experience with monitoring and observability tools such as Prometheus, Grafana, Dynatrace, or CloudWatch.
  • Proficiency in scripting and automation using Python, Bash, or similar languages.
  • Strong understanding of Git workflows, branching strategies, and version-control practices.
  • Knowledge of cloud security, networking, identity and access management, and infrastructure reliability principles.
  • Strong troubleshooting, communication, collaboration, and problem-solving skills.

Preferred Qualifications:

  • AWS, Kubernetes, or DevOps-related certifications.
  • Experience supporting enterprise-scale, highly available production environments.
  • Familiarity with GitOps, Helm, service mesh technologies, and container security.
  • Experience with incident management, disaster recovery, and business continuity practices.
  • Demonstrated ability to evaluate and adopt emerging technologies, including AI-assisted engineering tools.

Skills

AWS
Service Mesh
Apache
Bash
CDK
Git
Grafana
Helm
Jenkins
Kafka
Kubernetes
Prometheus
Python
Terraform

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