Cloud Infrastructure Engineer III
On-site · Columbus, Ohio, United States
Job Summary
Public Cloud Platform Engineer at JPMorgan Chase guides application teams on moving to the public cloud, supports production incidents, and provides primary operational engineering for the public cloud platform. Responsibilities include operating with AWS services (EC2, S3, RDS, CloudFront, EFS, CloudWatch, EKS), improving resiliency and security of cloud platforms, debugging and automating routine tasks, collaborating with cross-functional teams, driving onboarding readiness through resiliency tests and game days, and leveraging programming languages (Java, Python, SQL, Node, Go, Scala) along with containerization (Docker, Kubernetes) and IaC tools (CloudFormation, Terraform). The role emphasizes monitoring, performance optimization, and using DevOps tools (e.g., Ansible, Artifactory, Docker, GitHub, Jenkins, Kubernetes, Maven) across the SDLC, with exposure to multiple cloud platforms (AWS, GCP, Azure) and monitoring/observability tools (CloudWatch, Prometheus, Datadog). Preferred attributes include proactive problem-solving, a Site Reliability Engineering mindset, and a focus on running reliable production systems.
Required Qualifications
- Formal training or certification on software engineering concepts
- 3+ years applied experience
- A deep understanding of business technology drivers and their impact on architecture design, performance and monitoring, best practices
- experience/knowledge building or supporting web environments on AWS, which includes working with services like EC2, ELB, RDS, and S3
- Experience using DevOps tools in a cloud environment, such as Ansible, Artifactory, Docker, GitHub, Jenkins, Kubernetes, Maven etc.
- Experience across the SDLC process – Design and/or Development and/or support
- Experience/Knowledge using monitoring solutions like CloudWatch, Prometheus, Datadog
- Experience/Knowledge of writing Infrastructure-as-Code (IaC), using tools like CloudFormation or Terraform
- Experience with one or more public cloud platforms like AWS, GCP, Azure
- Experience with automation of Infrastructure tasks using Python or other languages
- Knowledge in leveraging AI/LLM tools to enable self-service on diagnosing infrastructure errors/failures
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