Manager-Digital Product Management

American Express•Atlanta, GA
•$103,750 - $174,750

About The Position

The Digital Workplace Product Group within American Express’s Technology organization delivers secure, scalable, and modern collaboration capabilities to colleagues across the enterprise. This product leadership role supports the roadmap, evaluation, and management of emerging AI-powered productivity capabilities, with a focus on Microsoft 365 Copilot, emerging Copilot experiences such as Cowork, Scout/Autopilot, and Code, and the broader Microsoft productivity ecosystem. The role operates at the intersection of AI, productivity, collaboration, technology, security, governance, and employee experience. It requires strong product-management discipline, deep Microsoft ecosystem knowledge, technical fluency, and the ability to evaluate emerging AI capabilities within the requirements of a highly regulated enterprise. The product manager supports product vision, roadmaps, and success measures; assesses new Microsoft capabilities for enterprise applicability and readiness; and works across product, engineering, architecture, identity, data, cybersecurity, and control functions. The role also establishes evaluation and readiness approaches for new AI capabilities and makes recommendations on piloting, deployment, restrictions, deferral, or additional controls.

Requirements

  • 5+ years of experience in Product Management, Technical Product Management, Enterprise Technology, or a related discipline.
  • Demonstrated experience owning enterprise digital, productivity, collaboration, SaaS, or AI products.
  • Deep knowledge of Microsoft 365 and the Microsoft productivity ecosystem.
  • Strong understanding of Microsoft 365 applications and colleague workflows across Teams, Outlook, Word, Excel, PowerPoint, OneDrive, and SharePoint.
  • Strong knowledge of Microsoft Copilot and AI-powered productivity experiences.
  • Strong understanding of generative AI concepts, including LLMs, grounding, prompting, agents, skills, plugins, model limitations, and responsible AI.
  • Technical fluency and demonstrated ability to engage effectively with engineering, architecture, cybersecurity, identity, and data teams.
  • Experience defining product strategies, roadmaps, requirements, prioritization frameworks, KPIs, and success measures.
  • Strong executive communication, analytical, organizational, and stakeholder-management skills.
  • Eligibility to work in the United States; the company will not pursue visa sponsorship for these positions.

Nice To Haves

  • Experience with emerging Microsoft Copilot experiences, including Cowork, Scout/Autopilot, Code, or comparable agentic AI capabilities.
  • Experience managing enterprise Microsoft 365 products, including Teams, Outlook, Word, Excel, PowerPoint, OneDrive, and SharePoint.
  • Experience with Microsoft AI and productivity product roadmaps and release-management practices.
  • Experience with enterprise AI assistants, agents, AI-powered search, and agentic workflows.
  • Experience with Microsoft Graph and integration concepts.
  • Experience with enterprise identity, permissions, information protection, data loss prevention, retention, and access controls within the Microsoft ecosystem.
  • Experience with AI evaluation, experimentation, testing, and measurement.
  • Experience with responsible AI, AI governance, data governance, and enterprise risk-management frameworks.

Responsibilities

  • Support the product vision, roadmap, and success metrics for Microsoft AI-powered productivity experiences.
  • Align roadmap decisions with colleague needs, enterprise priorities, technical dependencies, platform strategy, security requirements, and regulatory considerations.
  • Evaluate new Copilot capabilities, releases, and roadmap developments for enterprise applicability, readiness, dependencies, risks, and potential value.
  • Understand how different Copilot experiences intersect and develop a coherent product strategy across them.
  • Maintain deep product knowledge of the Microsoft 365 productivity ecosystem and how AI capabilities integrate across it.
  • Understand colleague experiences across Teams, Outlook, Word, Excel, PowerPoint, OneDrive, SharePoint, and other Microsoft productivity experiences.
  • Identify opportunities to create connected employee experiences across Microsoft 365 rather than treating applications as isolated products.
  • Understand dependencies between Copilot capabilities and the broader Microsoft 365 ecosystem, including identity, data, search, collaboration, and information architecture.
  • Work with product teams responsible for adjacent Microsoft capabilities to create a cohesive colleague experience.
  • Monitor changes across Microsoft's product portfolio and assess implications for product strategy and colleague experience.
  • Maintain a strong understanding of generative AI concepts and their application to enterprise productivity experiences.
  • Partner with engineering, architecture, identity, data, cybersecurity, and Microsoft technical teams.
  • Understand how Microsoft Copilot experiences interact with enterprise identity, permissions, information, applications, and organizational data.
  • Translate technical architecture, dependencies, platform limitations, and security considerations into product implications and decisions.
  • Evaluate product quality, reliability, usability, performance, and enterprise readiness.
  • Develop structured approaches for evaluating new Microsoft AI capabilities before enterprise deployment.
  • Define product readiness criteria addressing colleague value, functionality, technical readiness, security, privacy, compliance, accessibility, supportability, and operational readiness.
  • Partner with Information Security, Privacy, Legal, Compliance, Risk, Architecture, and other control functions.
  • Ensure product strategies and deployment decisions align with enterprise policies, responsible AI principles, and regulatory expectations.
  • Identify product risks, dependencies, control considerations, and potential unintended consequences associated with new AI capabilities.
  • Develop recommendations on whether capabilities should be piloted, broadly deployed, restricted, deferred, or require additional controls.
  • Maintain product artifacts and decision documentation that support governance and enterprise lifecycle management.
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