Senior Infrastructure Engineer I
About The Position
The Senior Infrastructure Engineer I builds resilient platforms, modernizes enterprise infrastructure, and enables AI at scale. The role involves engineering and operating bare-metal Kubernetes and containerized platforms, administering enterprise systems, delivering CI/CD and observability capabilities, supporting GPU-enabled AI inference environments, and maintaining data integration and big data platforms. It also leads change, release, incident response, production support, root-cause analysis, documentation, and knowledge transfer. The position requires extensive IT experience and deep knowledge of high-availability infrastructure and enterprise operations, including experience supporting business application systems in finance and health care environments. A master's degree in Computer Science or a similar field is required. Employment eligibility to work in the United States is required; American Express will not pursue visa sponsorship for these positions.
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 Google Cloud, Amazon Web or another public cloud variant; Unix, Linux, RHEL, Windows NT/XP/2000/2003 Server, VMware ESX, vSphere, UCS, and HPE infrastructure.
- Knowledge of Kubernetes, OpenShift, Rancher, Docker, Containerd, Kubespray, Kubeadm, Helm, Istio, and NGINX.
- Knowledge of GitLab, GitLab Runner, Jenkins, and Quay.
- Knowledge of Grafana, Kibana, Prometheus, Elasticsearch, Fluentd, Metricbeat, Filebeat, APM Server and agents, Weave Scope, Node Exporter, and DCGM Exporter.
- Knowledge of HashiCorp Vault, Vault Agent Injector, Raft storage, LDAP, Active Directory/ADS, Kubernetes secrets, and ACEs.
- Knowledge of 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 DB2 9.x/7.x, SQL Server 2005/2000, Netezza, and MySQL.
- Knowledge of MapR 4.x/5.x/6.x, HDFS, MapReduce, YARN, Oozie, Pig, Hive, HBase, Hue, Sqoop, and DistCp.
- Knowledge of shell scripting, kubectl, Kubernetes YAML, Control-M, Autosys, and Crontab.
- Familiarity with StackIQ, Satellite Server, UCS Intersight, Citrix, PuTTY, Cygwin X, ServiceNow, IBM Infoman, IBM Infoweb, and IBM ESR.
- HPE Data Fabric administration.
- Master's degree in Computer Science or a similar field.
- Eligibility to work 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, and Helm, including 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 HashiCorp Vault HA on Kubernetes with Vault Agent Injector, Kubernetes secrets, and Raft storage.
- Create end-to-end visibility with 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 with Prometheus, Grafana, Node Exporter, and DCGM Exporter.
- Install, upgrade, configure, and support MapR, Hadoop, IBM DataStage, and Infosphere Information Server platforms.
- Lead change, release, incident response, production support, root-cause analysis, documentation, and knowledge transfer.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
