Infrastructure Monitoring Lead Platform Engineer

Be a part of a talented engineering team that’s constantly pushing the envelope to build and deliver top-notch observability solutions

Assume a vital position as a key member of a high-performing team that delivers infrastructure and performance excellence. Your role will be instrumental in shaping the future at one of the world's largest and most influential companies. As a Lead Infrastructure Engineer at JPMorgan Chase within Enterprise Technology Infrastructure Platforms Monitoring team, you will help build and operate a strategic, market-leading Infrastructure Monitoring platform that strengthens critical service resilience and delivers trusted operational insights. You will be a hands-on technical contributor on an high-performing agile team, building secure, stable, and scalable observability solutions—turning telemetry into actionable insights, modernizing event-to-incident workflows, enabling automation and AIOps-driven reliability improvements aligned to the firm’s business objectives. Job responsibilities Engineer, operate, and continuously improve the firm’s Infrastructure Monitoring platforms, ensuring availability, performance, scalability, and security. Build and run enterprise-grade Infrastructure Monitoring capabilities across Linux, Windows, and complex Network estates, including platform-level onboarding and lifecycle management. Uses enterprise-authorized AI capabilities within the work environment to accelerate infrastructure analysis and design documentation, validating outputs and handling operational data according to sensitivity and security requirements. Design and implement platform services, integrations, and telemetry collection across metrics, logs, events, including OpenTelemetry collection patterns where applicable. Develop and maintain standardized onboarding patterns (agents/collectors, configurations, dashboards, alert policies) to accelerate safe adoption at scale. Improve monitoring signal quality and usability through baselining, threshold strategy, noise reduction, enrichment, and topology/context alignment. Develop secure, high-quality automation and production code; review, debug, and improve code/configuration written by others. Automate platform operations and reduce toil through scripting and CI/CD-driven configuration management; implement infrastructure-as-code deployment patterns Manage & maintain production health for the monitoring platform: lead triage, perform RCA, and deliver preventative engineering and resilience improvements. Partner with infrastructure, application, and SRE teams to align platform capabilities to SLIs/SLOs, operational readiness, and continuous improvement goals. Applies reuse-first, AI-assisted practices within delivery and automation routines to identify recurring issues and validate remediation options, ensuring changes are traceable/auditable and aligned to resiliency and security expectations. Required qualifications, capabilities, and skills Formal training or certification on infrastructure engineering concepts and 5+ years applied experience Proficiency with enterprise operating systems (Linux and/or Windows), including administration, troubleshooting, performance analysis, and operational best practices within regulated production environments. Proven hands-on experience delivering and operating enterprise-scale Infrastructure Monitoring solutions across Linux, Windows, and/or Network estates Solid understanding and hands-on implementation of observability and telemetry concepts , including metrics, logs, and events, with experience using OpenTelemetry collection patterns and integrating telemetry into Downstream components Proficiency in automation and engineering practices , including scripting and development with Python, Ansible, PowerShell / Bash, and applying CI/CD-driven workflows for controlled, secure, and repeatable change management. Experience developing, reviewing, debugging, and maintaining secure, high-quality production code and platform configurations, including automation supporting monitoring platforms and platform operations. Well-rounded experience in infrastructure across hardware platforms, operating systems, networking, storage, and databases (MS SQL Server, Oracle, Cassandra), including common deployment patterns, integration architectures, scaling and resiliency considerations, and performance assessment. Experience implementing Infrastructure-as-Code (IaC) and configuration management practices using tools such as Terraform, enabling standardized provisioning and scalable, repeatable deployments. Hands-on experience operating in hybrid infrastructure environments , including enterprise on-prem platforms and public/private cloud, with familiarity supporting and migrating monitoring capabilities across cloud boundaries. Demonstrated ability to improve monitoring signal quality through baselining, threshold strategy, noise reduction, enrichment, and topology/context alignment, supporting reliable event-to-incident workflows and operational insights. Demonstrated experience using enterprise-authorized AI capabilities within the work environment to support infrastructure engineering workflows with strong validation habits and awareness of data sensitivity. Ability to review and validate AI-assisted recommendations before implementation, escalating when uncertain and ensuring outcomes align to resiliency, security, and auditability expectations. Preferred qualifications, capabilities, and skills Hands on experience operating one or more enterprise monitoring platforms such as SCOM, Tivoli, SMARTS, IBM Instana, DX NetOps, ITNM ,Netcool Suite Experience with modern observability ecosystems such as Dynatrace, Grafana, Prometheus and interoperability patterns for telemetry integration, routing and visualization. Experience with Kubernetes (e.g., EKS) for container orchestration and operations. Experience with topology-driven monitoring and correlation approaches for large-scale infrastructure environments. Knowledge of Event Management & AIOps workflows (noise reduction, anomaly detection, probable cause analysis, guided remediation) with appropriate controls.