Director-Digital Product Mgmt - Enterprise AI Platforms

American Express•Sunnyvale, CA

About The Position

The Director of Product Management will own the strategy, multi-year roadmap, investment priorities, delivery, adoption, and measurable outcomes for a portfolio within American Express’s Enterprise AI Platform. The role determines where enterprise investment can remove common barriers to AI development, translates recurring customer and Forward-Deployed Engineering (FDE) learnings into reusable platform capabilities, and makes build, buy, partner, and standardization decisions. The objective is to help teams across American Express move AI use cases from experimentation to secure, scaled production more quickly, easily, and cost-effectively. The Director partners with Engineering, Architecture, Data Science, Security, Risk, FDE, and business teams, and leads product managers responsible for enterprise-scale AI capabilities. Success includes establishing a clear product strategy and investment thesis, increasing adoption and reuse of shared capabilities, reducing the time, cost, and complexity of building and operating AI applications, and demonstrating measurable improvements in developer productivity, platform economics, and enabled business value. The role owns product vision and discovery; roadmap and investment prioritization; product lifecycle and delivery; launch, adoption, and scale; measurement and continuous improvement; and product and people leadership. It requires balancing innovation and speed with enterprise security, privacy, risk, responsible AI, reliability, and operational requirements. The Director will develop product managers and future product leaders and foster customer focus, technical excellence, collaboration, and continuous learning.

Requirements

10+ years of progressive product management experience, including leadership experience building enterprise software, platforms, developer products, AI/ML products, or cloud technologies.
Proven experience defining product strategy and leading multi-year roadmaps for complex enterprise platforms.
Demonstrated success building and scaling products that enable other teams to develop differentiated customer or employee experiences.
Strong understanding of modern AI application architecture and the platform capabilities required to build, evaluate, deploy, govern, observe, and operate AI systems at enterprise scale.
Experience partnering deeply with Engineering to deliver highly technical platform capabilities.
Proven ability to influence senior stakeholders and drive alignment across complex, matrixed organizations.
Strong product judgment, including determining what should be standardized, abstracted, reused, purchased, or left to individual product teams while balancing customer, technical, operational, risk, and business considerations.
Excellent executive communication, storytelling, and presentation skills.

Nice To Haves

Experience leading product strategy for enterprise AI platforms, developer tools, ML infrastructure, or intelligent automation.
Experience building or scaling AI-powered products, LLM platforms, agentic systems, or AI orchestration capabilities.
Familiarity with modern AI platform capabilities such as model access and gateways, agent and tool integration, evaluation, retrieval and knowledge systems, prompt management, and AI observability.
Experience with enterprise AI governance, security, privacy, model risk management, and responsible AI.
Experience developing partnerships with hyperscalers, AI model providers, enterprise technology companies, or open-source communities.
Experience defining platform adoption strategies and measuring developer productivity, platform health, platform economics, and business value enabled.

Responsibilities

Own the product vision and strategy for a portfolio within the Enterprise AI Platform.
Identify recurring customer needs and translate enterprise AI and FDE learnings into scalable platform opportunities, distinguishing reusable capabilities from application-specific requirements.
Simplify the AI developer journey and establish scalable paved roads while preserving teams’ ability to innovate.
Evaluate emerging AI technologies and ecosystem shifts for their potential to improve customer outcomes, developer productivity, platform economics, enterprise reuse, and speed to production.
Own the product roadmap and prioritize investments based on customer value, developer productivity, technical feasibility, scalability, enterprise reuse, platform economics, and enabled business value.
Lead product trade-offs and build-versus-buy-versus-partner decisions, including sourcing capabilities from technology partners or open-source ecosystems.
Determine where the platform should provide enterprise standards and abstractions and where product teams should retain flexibility.
Align Product, Engineering, Architecture, Security, Risk, and business stakeholders around priorities, investments, and product outcomes.
Lead the product lifecycle from discovery through delivery with Engineering, Architecture, and FDE teams.
Deliver secure, scalable, and reliable platform capabilities, APIs, developer tooling, and reusable AI services that reduce the effort required to build and operate AI applications.
Balance innovation and speed with enterprise requirements for security, privacy, risk, responsible AI, reliability, and operational excellence.
Partner with FDE to accelerate adoption, solve high-value enterprise use cases, and identify platform gaps through direct engagement with internal customers.
Translate FDE implementations and customer learnings into reusable platform capabilities and patterns, distinguishing repeatable enterprise needs from use-case-specific requirements.
Drive adoption and reuse across engineering teams and business units by improving developer experience and removing barriers to production.
Define success metrics for adoption and reuse, developer productivity, time-to-production, platform health and reliability, platform economics, customer satisfaction, and business value enabled.
Use customer feedback, platform telemetry, and FDE insights to improve products and inform roadmap and investment decisions.
Measure whether platform investments reduce duplicated engineering effort, improve reuse, accelerate delivery, or improve AI application development and operating economics.
Build and lead a high-performing product organization, developing product managers and future product leaders and establishing operating mechanisms, accountability, and execution excellence.
Establish product practices and decision frameworks that drive strategic clarity and effective product decisions.
Build a culture of customer focus, technical excellence, collaboration, and continuous learning.