Agentic AI Infrastructure Engineer II - Core Platforms

Posted 3 Days Ago
Be an Early Applicant
3 Locations
Hybrid
Mid level
Fintech • Financial Services
The Role
Designs and operates scalable infrastructure for agentic AI, model training, inference, and distributed workloads. Responsibilities include Kubernetes and GPU platform engineering, infrastructure as code, high-performance storage and networking, observability, FinOps, security, capacity management, testing, documentation, and operational support. The role also integrates AI-assisted engineering and AIOps tools into deployment, monitoring, troubleshooting, and infrastructure workflows while partnering with AI, security, risk, and platform teams.
Summary Generated by Built In

The Enterprise Technology Services organization partners with every part of the American Express business to power the company’s growth and innovation with trust and efficiency, and drive competitive differentiation with speed. We support the delivery and operations of technology, digital, and data capabilities, platforms, and services globally. Specifically, our team is responsible for the company’s technology engineering, architecture, and infrastructure, providing 24x7 support to ensure an uninterrupted, high-quality experience for customers and colleagues. We also provide product management for core enterprise platforms, and lead technology risk and information security, enterprise data governance and platforms, digital product and design, and enterprise AI platforms on behalf of the company. 

The AI Infrastructure Engineer is responsible for designing, implementing, and maintaining robust, scalable, and efficient infrastructure solutions that support AI-enabled workloads. This role ensures infrastructure deployments align with technical standards and strategic objectives, proactively resolves operational issues, and provides clear documentation and expert technical support throughout the project lifecycle. 

 

Responsibilities
  • Designs the configuration and implementation of infrastructure deployments, ensuring adherence to predefined technical requirements and standards 

  • Develops and maintains comprehensive technical design and implementation documentation, ensuring detailed records facilitate seamless infrastructure project execution 

  • Supports platform infrastructure availability and performance, proactively identifying and resolving issues or anomalies to maintain optimal operational efficiency 

  • Conducts in-depth analysis of current state systems to gather detailed requirements and identify potential improvements in infrastructure design and deployment processes 

  • Integrates infrastructure components, ensuring they meet advanced robustness, scalability, and efficiency criteria, and aligning with strategic objectives 

  • Conducts test planning and execution activities, validating infrastructure solutions to ensure they meet both business and technical requirements 

  • Resolves technical issues encountered during the project lifecycle, providing expert problem-solving and escalating critical issues when necessary 

  • Coordinates with project teams to ensure infrastructure components are prepared for production, ensuring readiness and compliance with established standards and protocols 

  • Integrates AI-assisted tools and prompt engineering techniques into deployment, monitoring, and infrastructure support workflows to improve efficiency and reduce manual intervention, including validation of AI-generated recommendations, identification of infrastructure anomalies, capacity issues, and deployment risks, support for runbook generation, incident troubleshooting, postmortem summarization, log analysis, infrastructure environments hosting AI-enabled workloads, and operational activities requiring human oversight and approval.

  • Integrates ML-powered AIOps tools into deployment and monitoring workflows to detect anomalies, predict failures, and correlate incidents across distributed systems, including support for custom anomaly detection on metrics, logs, and traces.

  • Applies AI-assisted engineering tools such as GitHub Copilot, Claude Code, Cursor, and similar capabilities to develop, review, and improve infrastructure-as-code artifacts (e.g., Terraform, Ansible, Kubernetes manifests), including security and configuration validation prior to deployment.

  • Designs and operates GPU- and accelerator-enabled compute platforms, including cluster scheduling, workload placement, capacity management, quota and reservation controls, and utilization optimization.

  • Builds reusable platform capabilities for model training, fine-tuning, inference, and agentic workloads using Kubernetes, containers, infrastructure as code, and automated delivery pipelines.

  • Engineers high-performance storage, networking, and data-movement patterns required for distributed AI workloads, with measurable service-level objectives for availability, latency, throughput, and recovery.

  • Implements end-to-end observability and FinOps controls for AI infrastructure, including workload telemetry, accelerator utilization, cost attribution, anomaly detection, performance tuning, and capacity forecasting.

  • Partners with AI engineers, security, risk, and platform teams to establish secure multi-tenant isolation, identity and access controls, secrets management, software supply-chain controls, and operational readiness.

Qualifications
  • Experience designing infrastructure for AI agents, including agent runtimes, orchestration frameworks, tool integrations, asynchronous execution, and stateful workflows. Examples include LangGraph, Semantic Kernel, and comparable frameworks.

  • Experience applying Agentic AI tools to support infrastructure engineering, platform support, or cloud operations work, including reviewing AI-generated operational insights.

  • Experience validating AI-generated operational outputs and incorporating AI-enabled practices into infrastructure workflows, including AI-assisted operational recommendations requiring human review and approval.

  • 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 in different programming languages, DevOps tools such as Ansible, Puppet, Terraform, Python, Shell scripting and PowerShell, and their applications in infrastructure.

  • Experience in infrastructure components such as servers, storage, networking, and virtualization technologies.

  • Experience in network protocols and their job in infrastructure management. \

  • Experience in networking fundamentals.

  • Experience in databases such as DB2, SQL Server, Oracle, MySQL.

  • Experience in tools used in planning, analyzing, crafting, building, testing, configuring, and maintaining applications.

  • Experience in cloud platforms (e.g., AWS, Azure, Google Cloud).

  • Experience in monitoring technologies such as Prometheus, ElasticSearch and Grafana.

 

Education and Knowledge 

  •  3 to 5 Years of experience in infrastructure engineering, cloud engineering, DevOps, or a related technical field, including at least 2 years of hands-on experience 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.

  • Knowledge of storage management (e.g., SAN, NAS) design and support 

  • Knowledge of middleware technologies.

  • Knowledge of software defined networking, automation, and orchestration and their applications.

  • Knowledge of platform delivery methodology (Agile, Scrum, Agile XP, Best in Class Development, Waterfall, etc.).

  • Knowledge of scripting and automation skills (e.g., PowerShell, Bash, Python).

  • Knowledge of DevOps practices and tools (e.g., continuous integration/continuous deployment pipelines, Docker, Kubernetes).

  • Knowledge of cloud technologies.

  • Knowledge of Windows and Linux administration.

  • Working knowledge of AI-assisted infrastructure automation, observability, and deployment support capabilities, and infrastructure services commonly used to support AI-enabled workloads.

     

Employment eligibility to work with American Express in the U.S. is required as the company will not pursue visa sponsorship for these positions.

About Us

At American Express, our culture is built on a 175-year history of innovation, shared values and Leadership Behaviors, and an unwavering commitment to back our customers, communities, and colleagues. From delivering differentiated products to providing world-class customer service, we operate with a strong risk mindset, ensuring we continue to uphold our brand promise of trust, security, and service.

As part of Team Amex, you’ll experience our powerful backing with comprehensive support for your holistic well-being and many opportunities to learn new skills, develop as a leader, and grow your career. Here, your voice and ideas matter, your work makes an impact, and together, you will help us define the future of American Express.

About the Team

We back you with benefits that support your holistic well-being so you can be and deliver your best. This means caring for you and your loved ones' physical, financial, and mental health, as well as providing the flexibility you need to thrive personally and professionally:

  • 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

For a full list of Team Amex benefits, visit our Colleague Benefits Site.

American Express is an equal opportunity employer and makes employment decisions without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, disability status, age, or any other status protected by law. American Express will consider for employment all qualified applicants, including those with arrest or conviction records, in accordance with the requirements of applicable state and local laws, including the California Fair Chance Act, the Los Angeles County Fair Chance Ordinance for Employers, and the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance. For positions covered by federal and/or state banking regulations, American Express will comply with such regulations as it relates to the consideration of applicants with criminal convictions.

We back our colleagues with the support they need to thrive, professionally and personally. That's why we have Amex Flex, our enterprise working model that provides greater flexibility to colleagues while ensuring we preserve the important aspects of our unique in-person culture. Depending on role and business needs, colleagues will either work onsite, in a hybrid model (combination of in-office and virtual days) or fully virtually.

US Job Seekers - Click to view the “Know Your Rights” poster. If the link does not work, you may access the poster by copying and pasting the following URL in a new browser window: https://www.eeoc.gov/poster.


The below represents the expected salary range for this job requisition. Ultimately, in determining your pay, we’ll consider your location, experience, and other job-related factors.​

Skills Required

  • 3 to 5 years of experience in infrastructure engineering, cloud engineering, DevOps, or a related technical field
  • At least 2 years of hands-on experience supporting AI-enabled infrastructure, AI automation, or agentic AI technologies
  • Bachelor's degree in Computer Science, Information Technology, Engineering, or comparable experience
  • Experience designing infrastructure for AI agents, including runtimes, orchestration frameworks, tool integrations, asynchronous execution, and stateful workflows
  • Experience with agentic AI tools for infrastructure engineering, platform support, or cloud operations
  • Experience validating AI-generated operational outputs and recommendations
  • Experience with Kubernetes-based AI platforms, containers, workload schedulers, and GPU or accelerator orchestration
  • Experience operating model-serving or inference platforms and optimizing production AI workload performance, availability, and cost
  • 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, network protocols, and networking fundamentals
  • Experience with DB2, SQL Server, Oracle, or MySQL databases
  • Experience with AWS, Azure, or Google Cloud
  • Experience with Prometheus, Elasticsearch, and Grafana
  • Knowledge of application infrastructure, standards, middleware, storage management, software-defined networking, automation, and orchestration
  • Knowledge of DevOps practices, CI/CD pipelines, Docker, Kubernetes, cloud technologies, Windows administration, and Linux administration
  • Advanced degree

American Express Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about American Express and has not been reviewed or approved by American Express.

  • Fair & Transparent Compensation — Pay is considered generally solid for many, with frequent mentions of good compensation alongside strong benefits. Overall sentiment points to many employees feeling adequately paid even if it is not viewed as top-of-market.

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The Company
HQ: New York, NY
100,703 Employees
Year Founded: 1850

What We Do

At American Express, we know that with the right backing, people and businesses have the power to progress in incredible ways. Whether we’re supporting our customers’ financial confidence to move ahead, taking commerce to new heights, or encouraging people to explore the world, our colleagues are constantly striving to uphold our powerful backing promise to our customers and each other every day. These beliefs have been our North Star for 170 years as our business transformed – from helping evacuate travelers during World Wars, to ensuring the safety of our customers’ funds during the Great Depression in the U.S., to creating the Shop Small® movement to help small businesses recover from the Financial Crisis, to providing aid to communities impacted by many natural disasters and so much more. For generations, the key to our success has been the determination and resilience of our American Express colleagues. Now, as a globally integrated payments company, we work together to provide customers with access to products, insights and world-class experiences that enrich lives and build business success. Join us and let’s lead the way together.

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