Director-Digital Product Management - Enterprise AI Platforms
About The Position
American Express is seeking a Director of Product Management to own the strategy, multi-year roadmap, investment priorities, delivery, adoption, and measurable outcomes for a portfolio within its Enterprise AI Platform. The role will identify where enterprise investment can remove common barriers to AI development, turn recurring customer and Forward-Deployed Engineering (FDE) learnings into reusable platform capabilities, and make 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 will partner with Engineering, Architecture, Data Science, Security, Risk, FDE, and business teams, and lead product managers responsible for enterprise-scale AI capabilities. The portfolio includes foundational capabilities that enable teams to develop, deploy, govern, and scale AI products and experiences securely and responsibly. Success includes establishing a clear product strategy and investment thesis, increasing adoption and reuse, reducing the time, cost, and complexity of building and operating AI applications, and demonstrating measurable gains in developer productivity, platform economics, and business value. The position involves setting product direction, prioritizing investments, leading product development from discovery through delivery, driving launches and adoption, defining and using success metrics, and building a high-performing product organization. American Express describes its work model as onsite, hybrid, or virtual depending on the role and business need; the specific arrangement for this role is not stated.
Requirements
- At least 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 to standardize, abstract, reuse, purchase, or leave 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 standardized 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 impact on customer outcomes, developer productivity, platform economics, enterprise reuse, and speed to production.
- Own the product roadmap and prioritize investments according to customer value, developer productivity, technical feasibility, scalability, enterprise reuse, platform economics, and business value.
- Lead product trade-offs and build-versus-buy-versus-partner decisions, including decisions about internal development, technology partners, and open-source ecosystems.
- Decide where the platform should provide enterprise standards and abstractions versus where product teams should retain flexibility.
- Align Product, Engineering, Architecture, Security, Risk, and business stakeholders on priorities, investments, and outcomes.
- Lead the product lifecycle from discovery through delivery in partnership with Engineering, Architecture, and Forward-Deployed Engineering teams.
- Deliver secure, scalable, reliable platform capabilities, APIs, developer tooling, and reusable AI services that reduce the effort needed to build and operate AI applications.
- Balance innovation and speed with requirements for security, privacy, risk, responsible AI, reliability, and operational excellence.
- Partner with Forward-Deployed Engineering to accelerate adoption, address 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 enterprise-wide needs from use-case-specific requirements.
- Drive adoption and reuse across engineering teams and business units by improving developer experience and removing barriers to moving AI applications into production.
- Define success metrics covering adoption and reuse, developer productivity, time to production, platform health and reliability, platform economics, customer satisfaction, and business value.
- 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 the economics of developing and operating AI applications.
- Build and lead a high-performing product organization, develop product managers and future product leaders, and establish operating mechanisms, accountability, and execution excellence.
- Establish product practices and decision frameworks that support strategic clarity and effective decisions.
- Build a culture of customer focus, technical excellence, collaboration, and continuous learning.
Benefits
- 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 of paid parental leave for all parents, including 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 the Healthy Minds program
- Career development and training opportunities
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What This Job Offers
Job Type
Full-time
Career Level
Director
Education Level
No Education Listed
