JPMorgan Chase
Infrastructure Monitoring Lead Platform Engineer
$147K–$190K
Columbus, OH +2 · Full-time · Posted Oct 21, 2026
- Location
- Columbus, OH
Plano, TX
Jersey City, NJ - Experience
- 5+ years applied experience; formal training or certification is also required.
- Education
- Formal training or certification on infrastructure engineering concepts.
About the job
Builds and operates JPMorgan Chase’s enterprise infrastructure monitoring platform, improving observability, automation, and production resilience across infrastructure environments.
What you'll do
- Operate and improve monitoring platforms, telemetry collection, onboarding, and lifecycle management across infrastructure estates.
- Develop secure automation and infrastructure-as-code workflows; improve monitoring signal quality and event-to-incident processes.
- Lead production triage and root-cause analysis, deliver resilience improvements, and partner with infrastructure, application, and SRE teams.
What they ask for
- Formal training or certification in infrastructure engineering concepts.
- Experience with Linux and/or Windows administration, troubleshooting, and performance analysis in regulated production environments.
- Hands-on enterprise monitoring and observability experience, including metrics, logs, events, and OpenTelemetry collection patterns.
- Scripting and engineering experience with Python, Ansible, PowerShell / Bash, CI/CD, and Infrastructure-as-Code practices.
Nice to have
- Experience with enterprise monitoring or observability platforms such as SCOM, IBM Instana, Dynatrace, Grafana, or Prometheus.
- Experience with Kubernetes (e.g., EKS), topology-driven monitoring, or Event Management and AIOps workflows.
Pay
$147,250.00-$190,000.00 USD base salary
Tools
Linux, Windows, OpenTelemetry, Python, Ansible, PowerShell / Bash, Terraform, Kubernetes (e.g., EKS)
AI focus
Uses enterprise-authorized AI capabilities to support infrastructure analysis, documentation, delivery, and automation; validates recommendations and handles operational data according to sensitivity, security, resiliency, and auditability expectations.
Model-written summary · the original posting is authoritative