Senior Infrastructure Engineer I

American Express • Phoenix, AZ

2d

About The Position

The Senior Infrastructure Engineer builds resilient platforms, modernizes enterprise infrastructure, and enables AI at scale. The role spans bare-metal and cloud-native infrastructure, Linux and Unix administration, security, CI/CD, observability, data platforms, and production operations. The engineer supports enterprise systems, including environments in finance and health care, and leads work across the software development life cycle, from installation and configuration through deployment and production support.

Requirements

• 15+ years of IT experience across installation, configuration, administration, design, development, deployment, testing, and production support throughout the SDLC.
• Experience supporting business application systems in finance and health care environments.
• Deep knowledge of high-availability infrastructure, enterprise operations, release management, incident management, performance optimization, and production support.
• Experience with platforms including Google Cloud, Amazon Web or another public cloud, Unix, Linux, RHEL, Windows NT/XP/2000/2003 Server, VMware ESX, vSphere, UCS, and HPE infrastructure.
• Knowledge of cloud-native platforms including Kubernetes, OpenShift, Rancher, Docker, Containerd, Kubespray, Kubeadm, Helm, Istio, and NGINX.
• Knowledge of CI/CD and registries including GitLab, GitLab Runner, Jenkins, and Quay.
• Knowledge of observability tools including Grafana, Kibana, Prometheus, Elasticsearch, Fluentd, Metricbeat, Filebeat, APM Server and agents, Weave Scope, Node Exporter, and DCGM Exporter.
• Knowledge of security and secrets technologies including HashiCorp Vault, Vault Agent Injector, Raft storage, LDAP, Active Directory/ADS, Kubernetes secrets, and ACEs.
• Experience with ETL and data integration technologies including IBM DataStage 8.x/7.5x2/7.x/6.x EE and SE, MetaStage, Parallel Extender, Infosphere Information Server 8.0/8.1.1, Information Analyzer/ProfileStage, and QualityStage.
• Knowledge of databases including DB2 9.x/7.x, SQL Server 2005/2000, Netezza, and MySQL.
• Knowledge of big data technologies including MapR 4.x/5.x/6.x, HDFS, MapReduce, YARN, Oozie, Pig, Hive, HBase, Hue, Sqoop, and DistCp.
• Experience with automation and scheduling tools including shell scripting, kubectl, Kubernetes YAML, Control-M, Autosys, and Crontab.
• Familiarity with operations tools including StackIQ, Satellite Server, UCS Intersight, Citrix, PuTTY, Cygwin X, ServiceNow, IBM Infoman, IBM Infoweb, and IBM ESR.
• HPE Data Fabric administration experience.
• Master's degree in Computer Science or a similar field.
• Must be eligible to work with American Express in the United States; the company will not pursue visa sponsorship for these positions.

Responsibilities

• Build, administer, upgrade, scale, and troubleshoot bare-metal Kubernetes environments using Kubespray and Kubeadm, including highly available control planes, resource limits, persistent storage, secrets, YAML automation, kubectl scripting, and Horizontal Pod Autoscaling.
• Engineer containerized and microservices platforms using Kubernetes, Docker, Containerd, OpenShift, Rancher, Helm, and reusable Helm charts.
• Use Istio for observability, security, traffic management, routing, load balancing, fault tolerance, resilience, and context-based ingress routing.
• Operate GitLab, configure ADS authentication, maintain security and patching, automate upgrades, enable runners, and deliver CI/CD pipelines with Jenkins and Quay.
• Administer Linux, Unix, and RHEL systems through builds, upgrades, patching, migrations, scripting, troubleshooting, and root-cause analysis.
• Deploy and operate highly available HashiCorp Vault on Kubernetes using Vault Agent Injector, Kubernetes secrets, and Raft storage.
• Create end-to-end visibility using Elasticsearch, Fluentd, Metricbeat, Filebeat, Kibana, Prometheus, Grafana, APM agents, and Weave Scope.
• Design and deploy a standalone NGINX reverse proxy to distribute AI/LLM inference traffic across GPU-enabled worker nodes.
• Deploy and monitor NVIDIA A10 GPU environments using Prometheus, Grafana, Node Exporter, and DCGM Exporter.
• Install, upgrade, configure, and support MapR, Hadoop, IBM DataStage, and Infosphere Information Server platforms.
• Lead change, release, and incident response; provide production support and root-cause analysis; and produce documentation and knowledge transfer.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior