You are responsible for managing the creation and deployment of AI-enabled systems and tools that support the division’s work across strategic planning, measurement and learning, communications, and colleague engagement in service of our division’s desired impact. You serve as the product manager for a portfolio of internal AI-enabled products — executive decision-support tools, operational support tools, and more — developing and driving a product roadmap that connects individual tools to broader business needs, clarifies prioritization and sequencing, and translates those needs into practical solutions that are adopted and continuously improved. You have experience building or deploying AI-enabled workflows in professional settings and bring a systems-thinking orientation to connecting tools, data, and operational processes into cohesive experiences.

Responsibilities

• Identify needs for AI-enabled tools that support executive-level decision-making and strategic trade-offs; partner with the Data & AI Infrastructure team to build them or build them directly; manage handoffs carefully; and draw on deep familiarity with the USP’s strategies, impact goals, impact models, and governance processes to ensure tools reflect strategic and operational needs.

• Identify opportunities to address OOP-specific business needs — such as project management and pipeline tracking — and streamline OOP processes through automation and workflow improvements; prototype and experiment rapidly to test usability and validate need before committing to full development; and build and maintain the tools and operational systems that graduate from that process.

• Translate division strategy and measurement priorities into operational templates, shared systems and tools, and process documentation to enable consistent laddering of strategy, metrics, and analysis.

• Maintain and prioritize a queue of potential projects and feature requests; assess feasibility and sequencing; partner with OOP and division leadership teams to make clear decisions about what to build, when, and why; and hold yourself and partners accountable for follow-through on commitments.

• Drive adoption of new tools and workflows by developing user-facing guidance, facilitating onboarding, and actively soliciting feedback from a diverse range of colleagues — partnering where needed with the learning and engagement team — to ensure tools work for people across different roles, working styles, and levels of technical fluency. Contribute to division-wide learning and change efforts — including trainings, learning sessions, and other adoption activities.

• Approach ambiguous, fast-moving problem spaces with curiosity and a problem-solving orientation, treating incomplete information as an opportunity to build clarity rather than a reason to pause. Make thoughtful, strategic bets about where to invest deeply and where to move quickly, with an eye toward durability and scalability in an environment where AI tools and capabilities evolve rapidly.

• Communicate clearly across technical and non-technical audiences, translating complex AI concepts into accessible language and facilitating working sessions that advance alignment and decision-making.

• Contribute actively to a positive, inclusive team culture by seeking and giving feedback, supporting the development of colleagues by introducing and navigating new AI tools and workflows, and modeling the curiosity and openness you want to see in others.

Skillset

• Demonstrated experience building or deploying AI-enabled tools in a professional setting, with hands-on familiarity with large language models, prompt engineering, data infrastructure, retrieval-augmented generation, agentic workflows, evaluation, and the practical considerations involved in moving AI solutions from prototype to production.

• Significant experience working in close partnership with technical teams to translate non-technical business needs into scalable products and broad audiences.

• Significant experience owning the full lifecycle of internal tools or operational products, from prioritizing use cases and managing iterative development through driving adoption and continuous improvement.

• Experience navigating responsible AI, data privacy, security, and enterprise governance considerations in the context of product development — knowing when and how to engage relevant functions and incorporate their requirements into product decisions.

• Significant experience designing and maintaining operational templates, process documentation, shared systems, and fluency materials that support consistent strategy, metrics, and analysis across a complex organization.

• Experience working in or closely with large, matrixed organizations — particularly in philanthropy, public sector, or social impact settings — with a strong ability to build trust and alignment across teams and levels of seniority.

• Demonstrated experience understanding the needs of leadership and teams through product management, user research and testing, stakeholder interviews, and strategic discovery.

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