Ai Devops Engineer Jobs in Michigan (NOW HIRING)

We are looking for Senior DevOps Engineer for our client in Grand Rapids, Michigan. This is a contract role through the end of the year 2026 with the possibility of extension.

***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.

Collaboration and Technical Leadership

• Partner with development, QA, product, security, and infrastructure teams to define DevOps strategies and engineering best practices.
• Provide technical guidance on cloud architecture, automation, deployment, and operational readiness.
• Support knowledge sharing, documentation, and the continuous improvement of engineering standards.
• Promote a culture of automation, ownership, reliability, and continuous learning.

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.