Why This Role Stands Out
This on-site AWS DevOps Engineer role offers a fantastic opportunity to build scalable cloud platforms and cutting-edge CI/CD pipelines, perfect for those eager to deepen their expertise in Kubernetes, Terraform, and Python automation. If you're a mid-senior level engineer passionate about infrastructure as code and driving production reliability, you'll thrive in this platform engineering-focused position. Apply now to join a dynamic team and advance your career in cloud technologies.
Quick Overview
Job Description
DevOps Engineer (Advanced)
Location: Columbus, OH 100% Onsite Employment Type W2: Contract-to-Hire (CTH) Required Visa: & GC Education: Bachelor s Degree Required
Position Overview
We are seeking a highly skilled DevOps Engineer (Advanced) to join a core DevOps Platform Engineering team responsible for building scalable cloud platforms, infrastructure automation, CI/CD pipelines, Kubernetes platforms, and reliability solutions. The ideal candidate will have strong hands-on experience with AWS, Kubernetes, Python automation, GitOps, Terraform, Docker, Helm, and deployment strategies.
This is a hands-on engineering role focused on platform development, automation, production reliability, and infrastructure engineering rather than traditional system administration or infrastructure support.
Key Responsibilities
- Design, develop, and maintain scalable, secure, and highly available DevOps and cloud infrastructure solutions.
- Build and automate infrastructure using Terraform and Python-based operational tooling.
- Develop and maintain Kubernetes-based platforms using Kubernetes, Docker, Helm, and GitOps practices.
- Manage and support AWS container services, including EKS, ECS, and ECR.
- Design and implement automated CI/CD pipelines using tools such as Jenkins and GitLab CI.
- Implement GitOps-based deployment and infrastructure management practices.
- Develop Python automation scripts and operational tools to eliminate repetitive manual processes and improve system reliability.
- Implement and manage deployment strategies including rolling, blue/green, and canary deployments.
- Troubleshoot complex application, infrastructure, deployment, and production issues.
- Identify opportunities to automate recurring incidents and improve operational stability.
- Develop monitoring, observability, and reliability solutions using Prometheus and Grafana.
- Analyze application and infrastructure logs to support incident investigation and root-cause analysis.
- Develop and maintain infrastructure supporting ML platforms, model deployment, and automated ML pipelines.
- Collaborate with engineering, architecture, platform, and internal teams to evaluate technical solutions and improve platform capabilities.
- Develop high-quality production code and participate in code reviews, debugging, and technical design discussions.
- Support emerging AI/ML and Agentic AI initiatives, including AI-powered operational automation and intelligent troubleshooting solutions.
Required Skills
- 8+ years of relevant DevOps/Cloud/Platform Engineering experience
- Strong hands-on experience with AWS
- Hands-on experience with AWS EKS, ECS, and ECR
- Strong Kubernetes/K8s administration and production experience
- Strong experience with Docker and containerization
- Hands-on experience with Helm
- Strong understanding and implementation of GitOps
- Strong Python programming and automation experience
- Experience building operations and infrastructure automation tooling
- Hands-on experience with Terraform
- Strong understanding of CI/CD pipelines
- Experience with deployment strategies such as Rolling, Blue/Green, and Canary
- Strong production troubleshooting and technical problem-solving skills
- Ability to develop and maintain secure, high-quality production code
Preferred Skills
- Jenkins
- GitLab CI
- Prometheus
- Grafana
- Monitoring and observability
- Log analysis and production troubleshooting
- Platform Engineering
- Infrastructure as Code
- Multi-cloud environments
- Kubernetes-based ML platforms
AI / ML Preferred Experience
Experience in any of the following will be a strong advantage:
- AI Development
- MLOps
- ML Platform Engineering
- Kubeflow
- Agentic AI
- Generative AI
- RAG applications
- ML model deployment and monitoring
- Automated ML pipelines
- AI-powered operational tooling
Ideal Candidate
The ideal candidate is a hands-on DevOps, Platform, SRE, Cloud, or MLOps Engineer who can write production-quality Python code, automate infrastructure, manage Kubernetes platforms, implement GitOps, and build scalable AWS environments.
Candidates with experience combining DevOps + AWS + Kubernetes + Python + GitOps + Terraform, particularly in AI/ML or MLOps environments, will be highly preferred.
Interview Process
- 2 interview rounds
- Approximately 1 hour
- Live coding required
- Candidates must demonstrate strong hands-on technical and problem-solving abilities.
Important Requirements
- Bachelor s Degree required
- Must be willing to work 100% onsite in Columbus, OH
- Must be available Monday Friday, 9:00 AM 6:00 PM
- Must not require JPMC employer-sponsored immigration support
- Strong hands-on coding and automation experience required
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