Your Role

As the Senior Program Officer for Data & AI Infrastructure Integration, you will be at the forefront of transforming the education-to-workforce data and AI ecosystem to advance equity and opportunity for all learners. In this critical role, you will build and integrate crucial public good infrastructure to support evidence-based AI-native data system implementation that strengthens data feedback loops—helping district and postsecondary leaders access timely insights and collaborate more effectively across sectors to improve long-term regional outcomes

You are responsible for leading a research and development portfolio to test, co-develop, and refine integrated data and AI infrastructure solutions in real-world education and workforce contexts. You will design and lead iterative learning cycles at the intersection of the AI Infrastructure and System Feedback Loops (SFL) portfolios, generating actionable evidence about what conditions, infrastructure configurations, and integrated approaches accelerate impact for learners — particularly the most vulnerable populations. You will apply mastery-level expertise in implementation research and education data systems, and a proactive, solutions-oriented perspective to navigate ambiguity and drive thorough, equity-centered inquiry in partnership with grantees, researchers, and cross-divisional colleagues. 

What You’ll Do 

• Design and lead a portfolio of implementation R&D investments that test integrated plays between the AI Infrastructure and System Feedback Loops portfolios in real-world education and workforce contexts where baseline AI, data, and organizational readiness conditions exist. 

• Generate actionable evidence on the key infrastructure changes that promote efficacy, identifying what conditions — technical, organizational, and governance-related — are vital for integrated data and AI solutions to work as intended and drive measurable outcomes for learners.

• Design iterative learning cycles to assess whether integrated strategies accelerate progress toward division impact goals, and ensure findings are translated into concrete refinements to portfolio strategy and investment design.

• Test and validate theories of implementation in real-world contexts, surface where assumptions hold and where they require revision and communicate findings to division leadership and portfolio leads with rigor and clarity.

• Develop evidence and models that demonstrate benefits conferring beyond single localities or regions, building toward scalable, replicable approaches that can advise the broader field.

• Negotiate, implement, and lead a sophisticated portfolio of grants and performance-based contracts, applying an investor’s perspective and mastery-level knowledge of implementation research to ensure investments generate high-quality, actionable learning.

• Serve as the primary cross-portfolio integrator between the AI Infrastructure and SFL portfolios, ensuring that real-world implementation evidence directly informs how each portfolio refines its investment hypotheses, technical requirements, and theory of change — and that both portfolios are designed to learn from each other over time.

• Identify where AI Infrastructure and SFL investments have interdependent technical or programmatic requirements — such as the need for evaluation approaches to be designed in concert with the data systems that will collect outcomes — and broker the coordination needed to address those dependencies proactively.

• Review letters of inquiry and grant proposals; provide clear, concise, and insightful written analyses and recommendations for funding, including drafting and editing proposal summaries and progress reports for review by foundation leadership.

• Consult with grantees to achieve the desired impact of grants by conducting site visits, providing technical guidance, convening meetings of key collaborators, and applying and evaluating milestone-based performance objectives.

• Represent the foundation to key external constituencies and partners in implementation research, education data, and AI in education, staying informed on emerging signals and trends and contributing to field-level discourse.

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

• Ability to travel up to 35%.

Your Experience 

• An Advanced degree or equivalent demonstrated experience, preferably in education research, learning sciences, public policy, or a related field. 

• Mastery level knowledge of implementation research methodologies, including iterative learning cycles, theory of implementation, and approaches to testing and validating interventions in real-world contexts at scale. 

• Significant experience working with education-to-workforce data systems, including building, expanding, and/or using key federal, state, and private data sources, with deep knowledge of how data infrastructure intersects with AI deployment and learner outcomes. 

• Significant experience designing and leading sophisticated grant portfolios or R&D investment programs, with proven ability to generate actionable evidence and translate findings into strategy refinements. 

• Proven ability to make informed decisions that consider the impacts of data and technology on equity, particularly how AI can be developed and deployed to support and uplift Black, Latino, Indigenous students, and students from low-income backgrounds. 

• Significant experience building and sustaining partnerships across research, practice, and technology communities, with the ability to use informal influence and non-positional leadership to align diverse stakeholders around shared learning goals. 

• Proven excellence in synthesizing and communicating complex technical findings for diverse audiences, including foundation leadership, grantees, and external partners.