Lead Infrastructure Engineer - Powering Identity & Access Management at Scale

JPMorganChase•Columbus, OH

13d

About The Position

As a Lead Infrastructure Engineer in JPMorganChase’s CTO/IAM organization, you will be a key member of a high-performing team delivering infrastructure and performance excellence. You will apply deep knowledge of software, applications, and technical processes within infrastructure engineering, while continuing to develop technical and cross-functional expertise beyond your primary domain. You will lead infrastructure workstreams, help modernize technology and processes, and support reliable, secure, and well-monitored services. The role includes using enterprise-authorized AI capabilities to support infrastructure analysis, design documentation, automation, and operational workflows, while validating outputs and handling data in accordance with sensitivity and security requirements. You will also contribute to incident response, capacity and performance management, service-health targets, and automation of manual operational work.

Requirements

Formal training or certification in infrastructure engineering concepts and at least 5 years of applied experience.
Deep knowledge of one or more infrastructure engineering areas, such as hardware, networking terminology, databases, storage engineering, deployment practices, integration, automation, scaling, resilience, or performance assessment.
Demonstrated experience using enterprise-authorized AI capabilities in infrastructure engineering workflows, with strong validation habits and awareness of data sensitivity.
Ability to review and validate AI-assisted recommendations before implementation, escalate when uncertain, and ensure outcomes meet resiliency, security, and auditability expectations.
Deep knowledge of one specific infrastructure technology and scripting languages.
Deep knowledge of cloud infrastructure and multiple cloud technologies, with the ability to operate in and migrate across public and private clouds.
Experience with AWS, Kubernetes, Terraform, and/or Docker.
Practical cloud-native experience.
Experience with APM or observability platforms such as Dynatrace, Datadog, New Relic, or AppDynamics to monitor application and service health.
Experience conducting capacity and performance analysis to proactively identify scaling, tuning, or resilience risks.

Nice To Haves

Proficiency in designing, building, and deploying highly scalable software-based infrastructure components, such as cloud products, container systems, compute, storage, and network services.
Experience with one or more general-purpose programming languages, such as Go or Python.
Experience with scripting languages to automate tasks and build pipelines.
Experience designing and contributing to observability, performance, and capacity-management tools, such as Dynatrace, Grafana, or Splunk.
Experience resolving application-function and system customer-support issues.
Experience facilitating or contributing to post-incident reviews and problem-management practices to drive systemic reliability improvements.
Experience with CI/CD tooling and pipelines, such as Jenkins, GitLab CI, Spinnaker, or ArgoCD, to support automated build, test, and deployment workflows.

Responsibilities

Apply technical expertise and problem-solving methodologies to infrastructure projects of moderate scope, including design, development, and technical troubleshooting.
Use enterprise-authorized AI capabilities to accelerate infrastructure analysis and design documentation, validating outputs and handling operational data according to sensitivity and security requirements.
Drive a workstream or project involving one or more infrastructure engineering technologies, collaborating with other platforms to architect and implement changes that resolve issues and modernize technology and processes.
Consider upstream and downstream data, systems, and technical implications, and advise on mitigation actions.
Apply reuse-first, AI-assisted practices to delivery and automation routines to identify recurring issues and validate remediation options; ensure changes are traceable, auditable, resilient, and secure.
Troubleshoot priority incidents, facilitate blameless post-mortems, support issue closure, and participate in rotational support coverage as needed.
Define and drive adoption of monitoring frameworks for end-to-end application or service monitoring, appropriate telemetry, and noiseless alerting.
Contribute to products or software that automate manual operational work.
Monitor infrastructure and service capacity, performance, and utilization trends; identify risks and implement scaling or tuning actions before availability is affected.
Define and maintain service health and reliability targets, such as availability, latency, and error-rate thresholds, and drive engineering priorities to meet them.