Director-Digital Product Mgmt - Enterprise AI Platforms

American Express•Sunnyvale, CA

10h•$144,250 - $256,250

About The Position

American Express is seeking an experienced Director of Product Management to own strategy, the multi-year roadmap, investment priorities, delivery, adoption, and measurable outcomes for a portfolio within the Enterprise AI Platform. The role aims to make it faster, easier, and more cost-effective for teams across American Express to move AI use cases from experimentation to secure, scaled production by addressing common barriers, translating customer and Forward-Deployed Engineering (FDE) learnings into reusable capabilities, and making thoughtful build, buy, partner, and standardization decisions. The Director will work closely with Engineering, Architecture, Data Science, Security, Risk, FDE, and business teams, and lead product managers delivering enterprise-scale AI capabilities. The portfolio includes foundational capabilities that allow teams to develop, deploy, govern, and scale AI-powered 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 showing measurable gains in developer productivity, platform economics, and business value. American Express describes its Technology organization as supporting global capabilities and services, maintaining 24/7 servicing and availability, and driving differentiation through technology and data insights. The Enterprise AI Platform organization works with business and technology teams to shape AI strategy, develop scalable and reusable platforms, and support responsible AI innovation. Its Applied AI Innovation function evaluates emerging AI capabilities and partnerships to inform future platform capabilities and enterprise adoption. The position is supported by a benefits package that includes competitive base salary, bonus incentives, a company retirement-plan match, financial coaching, insurance and health benefits, paid parental leave, wellness and counseling resources, and career development and training opportunities. The job's expected salary range is referenced, but no amounts are supplied in the provided text.

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 deciding 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 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 enabled business value.

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 standardized reusable capabilities from application-specific requirements.
Find ways to 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 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 and where product teams should retain flexibility.
Align Product, Engineering, Architecture, Security, Risk, and business stakeholders around 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, and reliable platform capabilities, APIs, developer tooling, and reusable AI services that reduce the effort of building and operating AI applications.
Balance innovation and speed with enterprise 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.
Turn 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 moving AI applications from experimentation to production.
Define success metrics for adoption and reuse, developer productivity, time to production, platform health and reliability, platform economics, customer satisfaction, and enabled 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 product 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