60 American Express Jobs Hiring Near You

• 8+ years of product management experience, with significant experience leading platform, API, developer platform, or infrastructure products.

• Proven experience defining product strategy and delivering large-scale platform capabilities across multiple stakeholder groups.

• Experience building developer-facing products, APIs, SDKs, or ecosystem platforms.

• Strong understanding of authentication, authorization, identity, OAuth, consent management, platform security, and data governance concepts.

• Experience working across legal, compliance, privacy, and risk stakeholders to launch customer-facing platform capabilities.

• Demonstrated ability to operate effectively in highly cross-functional environments and influence without direct authority.

• Experience defining product metrics, experimentation frameworks, and data-driven decision-making processes.

• Excellent written and verbal communication skills, including the ability to translate complex technical concepts into clear business outcomes.

• Bachelor's degree or equivalent experience.

• Experience working with Large Language Models (LLMs), AI agents, agentic systems, MCP, function calling, tool orchestration, or related technologies.

• Experience building products for developer ecosystems, partner integrations, marketplaces, or platform businesses.

• Knowledge of MCP standards, agent frameworks, AI tooling ecosystems, and emerging industry patterns.

• Experience defining AI governance, responsible AI controls, model evaluation frameworks, or AI platform standards.

• Experience defining observability, telemetry, monitoring, analytics, or platform measurement capabilities.

• Familiarity with personalization platforms, customer context systems, conversational AI experiences, or AI-driven recommendation capabilities.

• Experience partnering with security, identity, privacy, and enterprise architecture organizations on platform-scale initiatives.

• Experience leading products in highly regulated industries such as financial services, payments, fintech, or technology.

• Advanced degree in Business, Computer Science, Engineering, or related field.

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

Define and Lead MCP Platform Strategy

• Own the product vision, strategy, and roadmap for the American Express MCP platform. 

• Define the foundational capabilities required to expose American Express services to external LLMs, AI assistants, agent platforms, and internal AI experiences. 

• Establish platform standards, governance models, and operating principles for MCP adoption across the enterprise. 

• Drive alignment across engineering, architecture, security, risk, compliance, privacy, and product teams to deliver scalable platform capabilities. 

• Evaluate emerging MCP standards, agent ecosystems, and industry developments to continuously evolve the platform strategy. 

Build the MCP Center of Excellence

• Serve as the company-wide expert on MCP architecture, implementation patterns, and agent integration best practices. 

• Develop frameworks, guidance, and reusable patterns that enable teams to build high-quality MCP capabilities consistently. 

• Define standards for tool design, metadata structures, descriptions, prompts, schemas, and agent interactions. 

• Establish governance processes that ensure MCP capabilities are discoverable, maintainable, and optimized for AI consumption. 

• Drive education, enablement, and adoption efforts across product and engineering organizations. 

Define Developer Experience and Integration Standards

• Own the MCP developer experience for both internal and external consumers. 

• Establish documentation standards, onboarding experiences, reference architectures, SDK requirements, and integration frameworks. 

• Define how developers, partners, and AI platforms discover, authenticate, and integrate with American Express MCP capabilities. 

• Lead experimentation with emerging integration models, including web-based MCP architectures and next-generation agent connectivity patterns. 

• Drive continuous improvements to usability, adoption, and integration success rates. 

Define Platform Foundations, Security, and Governance

• Partner with security, identity, and platform engineering teams to define authentication and authorization models for MCP-enabled experiences. 

• Establish standards for OAuth, consent management, permissioning, access controls, and customer data protection. 

• Define scalable approaches for customer identity resolution, authorization management, and secure agent interactions.

• Establish product principles and governance frameworks that define how American Express data, services, and customer information may be accessed and utilized by LLMs and AI agents.

• Partner with legal, compliance, privacy, risk, and data governance teams to ensure platform capabilities align with regulatory requirements, customer expectations, and company policies.

• Define standards for data minimization, consent, transparency, attribution, and appropriate AI usage.

• Drive platform capabilities that enable policy enforcement, auditability, and governance across agent interactions.

Establish Quality, Evaluation, Analytics, and Observability Frameworks

• Define evaluation methodologies to assess MCP tool quality, usability, discoverability, reliability, and effectiveness.

• Develop measurement frameworks that assess how well tools perform across various LLMs, agent platforms, and use cases.

• Partner with data science and analytics teams to establish KPIs, reporting, and performance monitoring capabilities.

• Lead the development of platform-wide observability, telemetry, debugging, and monitoring solutions.

• Drive continuous improvement through experimentation, measurement, and iterative optimization.

Build Personalization and Intelligence Foundations

• Define platform capabilities that enable personalization and contextual intelligence across AI-enabled experiences.

• Partner with data, AI, and product teams to establish reusable customer context, preference, and memory frameworks.

• Identify opportunities to improve agent effectiveness through shared context and personalization services.

• Ensure personalization capabilities are implemented responsibly and align with privacy and regulatory requirements.

Partner Across Product and Engineering Organizations

• Collaborate closely with MCP use case teams and business owners responsible for building individual customer experiences and MCP tools.

• Provide consultation, architectural guidance, and platform support throughout the product development lifecycle.

• Influence roadmaps across multiple organizations to ensure consistency and alignment with platform standards.

• Work closely with engineering leaders to prioritize investments that maximize platform adoption and long-term scalability.

• Build strong relationships across product, engineering, architecture, security, risk, legal, and operations teams.