Role : AI Product Owner
Location : 2 days onsite in NYC
Contract : 12+ Months
Interview : Video
The AI Product Owner is responsible for defining, prioritizing, and delivering AI-enabled products and services across a complex global organization. This role sits at the intersection of business strategy, technology delivery, governance, and operational execution, with a strong focus on applying AI to improve productivity, decision-making, knowledge management, risk oversight, and service delivery outcomes.
This is a business-facing product leadership role rather than a deep technical engineering position. It requires strong stakeholder engagement across senior leadership, delivery teams, data and technology specialists, and operational users in a federated environment. The role ensures AI initiatives are aligned to organizational priorities, delivered effectively, and adopted at scale.
Key Responsibilities
AI product strategy and roadmap
- Define and maintain the enterprise AI product roadmap aligned to organizational priorities.
- Translate business needs into practical AI use cases and deliverable solutions.
- Identify opportunities for automation, augmentation, and process simplification.
- Prioritize initiatives based on value, risk, complexity, and adoption readiness.
- Balance short-term delivery with long-term capability development.
Stakeholder engagement
- Partner with business, operations, legal, HR, communications, security, and technology teams.
- Facilitate workshops to capture requirements and identify pain points.
- Build alignment across a federated organization through influence and collaboration.
- Communicate AI opportunities, constraints, and risks in clear business terms.
- Support change management and training in coordination with delivery teams.
Product ownership and delivery
- Own and manage the AI product backlog and prioritization process.
- Define user stories, acceptance criteria, and measurable success outcomes.
- Collaborate with engineering, architecture, data, and cyber security teams.
- Support agile delivery practices including sprint planning and backlog refinement.
- Oversee pilots, proof-of-concepts, and scaled production deployments.
AI governance and risk
- Ensure AI solutions comply with ethical, legal, privacy, and security standards.
- Support development and enforcement of AI governance frameworks and controls.
- Work with security and legal teams on data usage, model risk, and third-party considerations.
- Monitor and address AI-related risks including bias, hallucinations, data leakage, and misuse.
Adoption and change management
- Drive adoption and realization of AI-enabled value across the organization.
- Develop training materials, communications, and user guidance.
- Establish feedback loops and usage reporting mechanisms.
- Promote responsible and effective use of AI tools across business functions.
Data and integration
- Collaborate with enterprise architecture and data teams to ensure AI-ready data foundations.
- Support integration of AI capabilities across enterprise platforms and systems.
- Promote API-led and scalable integration approaches.
Performance and reporting
- Define KPIs and success measures for AI initiatives.
- Track and report on adoption, efficiency gains, and risk outcomes.
- Present progress updates to senior leadership and governance forums.
Skills and Experience
Essential
- Experience as a Product Owner, Product Manager, or Digital Lead delivering enterprise technology products.
- Understanding of AI concepts including generative AI, copilots, automation, and LLM-based systems.
- Experience working in complex, multi-stakeholder global organizations.
- Strong facilitation, communication, and stakeholder management skills.
- Experience working in agile delivery environments.
- Ability to translate business requirements into technology outcomes.
- Understanding of data governance, privacy, and cybersecurity principles.
Desirable
- Experience in mission-led organizations such as NGOs, foundations, or international development.
- Exposure to Microsoft AI ecosystem (Copilot, Azure AI, Power Platform, Purview).
- Familiarity with enterprise architecture and integration patterns.
- Experience defining AI governance or responsible AI frameworks.
- Experience managing third-party vendors and technology partners.
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