Infrastructure Engineer II – Core Platforms

American Express

. Design infrastructure deployment configurations and implementations in accordance with technical requirements and standards .

Posted 10/14/2026full-timeUnited StatesMid-LevelSenior💰 $89,250 - $150,250 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and implementing AI-enabled infrastructure solutions, with a strong focus on Kubernetes, Ansible, Terraform, and cloud platforms. Proficient in optimizing performance, reliability, and cost for production AI workloads while integrating observability and FinOps practices.

Highest-signal resume keywords

Kubernetes-Based AI PlatformsAnsible, Terraform, PuppetAI Infrastructure DesignCloud Platforms (AWS, Azure, Google Cloud)Observability and FinOps Practices

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Infrastructure DesignAI Tools IntegrationDistributed Training InfrastructureHigh-Performance NetworkingCapacity PlanningSecurity and Reliability EngineeringObservability PracticesCloud OperationsShell ScriptingDatabase Management (DB2, SQL Server, Oracle, MySQL)

Tools & Technologies

GitHub CopilotClaude CodeCursorPrometheusElasticSearchGrafanaDockerVirtualization TechnologiesAI-Assisted ToolsAI-Enabled Practices

Industry Keywords

AI InfrastructureMulti-Tenant IsolationAgile MethodologiesDevOps PracticesInfrastructure as CodeCloud EngineeringIncident TroubleshootingOperational ReadinessWorkload SchedulingMiddleware

Tech Stack

Tools & technologies

AnsibleAWSAzureCloudDistributed SystemsDockerElasticSearchGrafanaKubernetesLinuxMySQLOraclePrometheusPuppetPythonShell ScriptingSQLTerraform

About the role

Key responsibilities & impact

Design infrastructure deployment configurations and implementations in accordance with technical requirements and standards
Develop and maintain comprehensive technical design and implementation documentation
Support platform infrastructure availability and performance by identifying and resolving issues or anomalies
Analyze current-state systems to gather requirements and identify infrastructure design and deployment improvements
Integrate infrastructure components for robustness, scalability, efficiency, and strategic alignment
Plan and execute tests to validate infrastructure solutions against business and technical requirements
Resolve technical issues throughout the project lifecycle and escalate critical issues when necessary
Coordinate with project teams to prepare infrastructure components for production
Integrate AI-assisted tools and prompt engineering into deployment, monitoring, and infrastructure support workflows
Validate AI-generated recommendations and identify infrastructure anomalies, capacity issues, deployment risks, and operational issues
Support runbook generation, incident troubleshooting, postmortem summarization, log analysis, and human-reviewed operational activities
Integrate ML-powered AIOps tools for anomaly detection, failure prediction, and incident correlation across distributed systems
Apply GitHub Copilot, Claude Code, Cursor, and similar tools to develop and validate Terraform, Ansible, and Kubernetes infrastructure-as-code artifacts
Design and operate GPU- and accelerator-enabled compute platforms, including scheduling, workload placement, capacity management, quotas, reservations, and utilization optimization
Build reusable Kubernetes and container-based platform capabilities for model training, fine-tuning, inference, and agentic workloads
Engineer high-performance storage, networking, and data-movement patterns for distributed AI workloads
Implement observability and FinOps controls covering telemetry, accelerator utilization, cost attribution, anomaly detection, performance tuning, and capacity forecasting
Partner with AI engineering, security, risk, and platform teams on multi-tenant isolation, access controls, secrets management, supply-chain controls, and operational readiness

Requirements

What you’ll need

Experience designing infrastructure for AI agents, including agent runtimes, orchestration frameworks, tool integrations, asynchronous execution, and stateful workflows; examples include LangGraph and Semantic Kernel
Experience applying Agentic AI tools to infrastructure engineering, platform support, or cloud operations, including reviewing AI-generated operational insights
Experience validating AI-generated operational outputs and incorporating AI-enabled practices into infrastructure workflows
Experience with Kubernetes-based AI platforms, containers, workload schedulers, and GPU or accelerator orchestration in cloud or hybrid environments
Experience operating model-serving or inference platforms and optimizing throughput, latency, availability, and cost for production AI workloads
Experience with distributed training or inference infrastructure, high-performance networking and storage, accelerator telemetry, and capacity planning
Experience implementing security, reliability engineering, observability, and FinOps practices for multi-tenant AI infrastructure
Experience with Ansible, Puppet, Terraform, Python, Shell scripting, and PowerShell
Experience with servers, storage, networking, virtualization technologies, and network protocols
Experience with databases such as DB2, SQL Server, Oracle, and MySQL
Experience with cloud platforms such as AWS, Azure, and Google Cloud
Experience with monitoring technologies such as Prometheus, ElasticSearch, and Grafana
3 to 5 years of experience in infrastructure engineering, cloud engineering, DevOps, or a related technical field, including at least 2 years supporting AI-enabled infrastructure, AI automation, or agentic AI technologies
Bachelor's degree in Computer Science, Information Technology, Engineering, and/or comparable experience; advanced degree preferred
Knowledge of application infrastructure and standards, storage management, middleware, software-defined networking, automation, and orchestration
Knowledge of Agile, Scrum, Agile XP, Waterfall, or comparable platform delivery methodologies
Knowledge of DevOps practices and tools, CI/CD pipelines, Docker, Kubernetes, and cloud technologies
Knowledge of Windows and Linux administration
Working knowledge of AI-assisted infrastructure automation, observability, deployment support, and infrastructure services for AI-enabled workloads
Employment eligibility to work with American Express in the U.S. is required; the company will not pursue visa sponsorship

Benefits

Comp & perks

Competitive base salaries
Bonus incentives
6% Company Match on retirement savings plan
Free financial coaching and financial well-being support
Comprehensive medical, dental, vision, life insurance, and disability benefits
Flexible working model with hybrid, onsite or virtual arrangements depending on role and business need
20+ weeks paid parental leave for all parents, regardless of gender, offered for pregnancy, adoption or surrogacy
Free access to global on-site wellness centers staffed with nurses and doctors (depending on location)
Free and confidential counseling support through our Healthy Minds program
Career development and training opportunities