Principal Architect, Enterprise Architecture

American Express•New York, NY

About The Position

Enterprise Architecture at American Express translates business priorities into technology direction, establishes reusable and secure architectural patterns, guides critical technology decisions, and embeds architecture into delivery. Its work spans Architecture as Code, Architecture as Design, Governance & Testing, and Business Architecture. The Principal Architect will lead AI-enabled architecture strategy across areas including agentic security and platform enablement (including the MCP ecosystem), AI-led global servicing and conversational technology, low-latency and critical payment platforms, and API and architectural best practices. The role also supports Business-Unit architecture initiatives for Global Servicing and Technology and International Card Services, while operating horizontally across the portfolio supported by Enterprise Architecture. This leader will shape how AI and agentic capabilities are incorporated into platforms, products, and architectural decisions. They will establish reference architectures, reusable patterns, engineering guardrails, and evaluation practices for secure, responsible, enterprise-scale adoption. The role partners with technology leaders, engineers, architects, product teams, domain experts, and governance functions to identify and prioritize opportunities, influence technical direction, and turn emerging AI capabilities into practical solutions. The successful candidate will combine deep architecture expertise with hands-on knowledge of modern AI systems and be effective at both strategic and technical levels. They will influence across a matrixed organization, communicate complex decisions clearly to senior leaders, and demonstrate proposed architectures through prototypes or scaled production implementations. The role builds on expectations for thought leadership, architectural reviews, enterprise standards, AI and automation, and horizontal influence.

Requirements

15+ years of progressive experience in technology architecture, software engineering, or a comparable discipline in a large-scale, complex environment.
Demonstrated experience designing and delivering enterprise-grade platforms, products, or technology capabilities.
Deep knowledge of large-scale system architecture, including distributed systems, APIs, cloud-native platforms, data-intensive applications, and hybrid technology environments.
Bachelor’s degree in computer science, computer science engineering, or a related field.
Experience defining or implementing enterprise AI architecture, including generative AI, machine learning, intelligent automation, or agentic systems.
Deep understanding of production-grade, scalable AI system considerations, including scalability, latency, reliability, security, observability, evaluation, lifecycle management, and cost optimization.
Experience creating reference architectures, reusable patterns, technical standards, architecture decision records, and engineering guardrails.
Experience creating OKRs, ROIs, and architectural assessments.
Experience developing and governing architecture standards, guidelines, and Architecture Decision Records (ADRs).
Proven ability to influence senior leaders, architects, engineers, product teams, and governance functions across a complex, matrixed organization.
Ability to operate as a horizontal technical leader and complex-platform and technical-product manager, influencing multiple teams and domains without direct ownership and driving alignment across matrixed organizations.
Demonstrated outcome-oriented leadership, including managing large and complex programs within time and budget constraints.
Employment eligibility to work with American Express in the U.S.; the company will not pursue visa sponsorship for these positions.

Nice To Haves

Advanced degree preferred.
Experience from leading technology or AI-forward organizations, with the ability to bring external perspectives and translate emerging innovations into enterprise-scale solutions.

Responsibilities

Define and advance AI and agentic platform architecture strategy, focusing on agentic security, MCP ecosystem enablement, flexibility to expand to SaaS providers, and maturation of home-grown AI capabilities.
Support architecture needs across Global Servicing & Corporate Technology, International Consumer Services Technology, and other Lines of Business, with relevance to financial services and payments.
Provide hands-on architectural thought leadership and expertise for complex or novel AI use cases, from early exploration through production deployment and scale.
Establish reference architectures, reusable patterns, standards, and guardrails for generative AI, agentic systems, intelligent automation, and related emerging technologies.
Ensure AI architectures align with enterprise standards and applicable security, privacy, risk, compliance, regulatory, and model-governance requirements.
Shape technical direction for AI-enabled platforms and capabilities, aligning near-term delivery with long-term business and enterprise architecture objectives.
Identify and prioritize high-impact AI opportunities that improve automation, customer and colleague experiences, operational efficiency, resilience, and system performance.
Influence enterprise architecture standards and contribute to the continued evolution of the Enterprise Architecture Playbook.
Lead architecture reviews and provide actionable guidance to improve design quality, reduce risk, and accelerate responsible adoption.
Define measurable architecture outcomes and use metrics, assessments, and OKRs to demonstrate adoption, architectural health, risk reduction, and business impact.
Lead prototypes and production implementations for mission-critical systems, demonstrating builder capabilities.
Bring experience in modernization and program management of complex platforms and ecosystems.
Communicate complex AI and architecture concepts clearly and actionably to technical and executive audiences.
Mentor architects and senior engineers, strengthening AI architecture capabilities and engineering practices across the organization.
Lead large and complex programs while driving outcomes within time and budget constraints.