Senior Program Officer, Portable Memory & Context (24-Month LTE) at Gates Foundation

Application Deadline: Friday, April 24th

*This position is a limited-term position for 24-months. Relocation will be provided

Your Role

As the Senior Program Officer, Portable Memory & Context, you will lead investments focused on building the emerging portable memory and context infrastructure required for next-generation AI systems in education and workforce pathways. You will drive progress on the technical, standards, and governance foundations needed to enable user-controlled, interoperable, and longitudinal memory systems.

Operating at the intersection of AI infrastructure, data ecosystems, and public-interest governance, you will identify where coordinated investment can unlock system-level capabilities that no single actor can build alone. This role requires defining ambiguous problem spaces, aligning stakeholders across sectors, and translating early-stage technical architectures into scalable, field-ready infrastructure with broad impact.

What You’ll Do

• Develop and manage a portfolio advancing the end-to-end memory stack across education-to-workforce pathways, enabling persistent, portable learner and worker context through investments in identity, storage, memory management, agent integration, and governance.

• Translate architecture into investable strategies: Identify where technical gaps (e.g., evaluation of longitudinal memory, provenance, agent orchestration, local-first constraints) require targeted funding, standards development, or field-building.

• Drive standards and ecosystem alignment: convene partners across frontier AI labs, EdTech, workforce systems, and standards bodies to advance shared schemas, protocols, and portability frameworks, avoiding fragmented or siloed implementations.

• Broker across technical and institutional layers: connect model developers, infrastructure providers, public sector actors, and product teams to ensure memory systems are usable across real-world education and workforce contexts

• Identify and advance priority AI infrastructure layers for education and workforce systems: shape investments across shared components (e.g., data pipelines, evaluation systems, model adaptation, and deployment infrastructure) that enable multiple downstream use cases.

• Identify and assess emerging technologies and standards that support interoperability across education-to-workforce ecosystems.

• Build knowledge base and thought leadership around context-aware, learner-centered data solutions.

• Serve as a technical resource to the division on AI infrastructure for education and workforce systems, including data, models, evaluation, and interoperability.

• Negotiate, execute, and manage a complex portfolio of grants or performance-based contracts.

• Consult with grantees and other partners to maximize project impact and ensure grants meet strategy goals. This may include site visits, providing operational guidance, and convening meetings of key stakeholders.

• Represent the foundation to key program-related external constituencies, as appropriate, on committees related to area of expertise and responsibilities of the position.

• Support inclusive culture through modeling behaviors and actions; escalate issues in a timely fashion to appropriate stakeholders.

Your Experience

• An advanced degree or equivalent demonstrated experience, preferably in a related field.

• Experience working across education and workforce systems, with an understanding of how data and AI can support transitions, mobility, and outcomes across the learner-to-earner lifecycle

• Deep experience and technical credibility in AI and data infrastructure, with a strong understanding of how systems are designed, integrated, and scaled across components and use cases.

• Experience with portable data and interoperable systems, and how they enable AI systems to leverage persistent, cross-context memory (e.g., identity frameworks, open standards, retrieval systems, agent architectures).

• Track record of operating in emerging, ambiguous technical spaces, translating early architectures into concrete investments, partnerships, or products.

• Experience convening and aligning multi-sector ecosystems (e.g., technology providers, public agencies, standards bodies), particularly where incentives are misaligned.

• Strong understanding of governance, privacy, and trust frameworks, and how they must be embedded into system design.

• Ability to assess where infrastructure should be standardized vs. differentiated, and where fragmentation poses systemic risk.

• Proven ability to translate complex technical concepts into actionable strategy and investment decisions across organizational boundaries

• Proven ability to lead complex portfolios and influence strategy across teams and external partners.

• Understanding of how diverse communities and partners engage with AI and data systems in education and workforce contexts, and ability to incorporate their needs into infrastructure design and investment decisions.