Senior Advisor, AI

The Abdul Latif Jameel Poverty Action Lab (J-PAL) is a global research center working to reduce poverty by ensuring that policy is informed by scientific evidence. Anchored by a network of over 390 affiliated professors at universities around the world, J-PAL conducts randomized impact evaluations to answer critical questions in the fight against poverty.

The Policy and Communications Group is a rapidly growing group within J-PAL working to translate research by J-PAL affiliates into actionable poverty alleviation policies around the world. As AI and machine learning increasingly reshape the landscape of international development, from predictive analytics in social protection to LLMs in education, J-PAL is seeking an Senior Advisor to lead its AI work portfolio across research, policy, and capacity building to ensure applications of AI in development are evidence-based and responsible.

This role is designed for a highly experienced senior leader who can provide strategic direction to J-PAL's global AI portfolio. This portfolio focuses on evaluating and scaling transformative applications of AI in development programs, advancing the field of AI and development economics research through randomized controlled trials, incorporating AI into J-PAL’s capacity building programs, and advising researchers and staff on leveraging AI to improve the quality and efficiency of J-PAL’s research, policy, and operations.

The Senior Advisor will report to the Global Executive Director and work closely with J-PAL’s AI Faculty Co-Chairs, AI, and policy teams. The Senior Advisor will serve as the staff lead for J-PAL’s AI regranting initiatives, including managing Project AI Evidence (PAIE), and supervising the PAIE team and other colleagues contributing to J-PAL’s AI portfolio.

The position is based in Cambridge, MA or Silicon Valley, CA with frequent travel to Cambridge. Hybrid or remote arrangements may be considered in accordance with MIT/J-PAL policy. Visa sponsorship is not available for this position. Only applications following all instructions at the bottom of this page will be considered.

Work closely with J-PAL’s Global Executive Director and AI Faculty Co-Chairs to help shape and advance an ambitious vision and strategy for J-PAL’s rapidly expanding AI work. Lead a team managing J-PAL's "AI for Social Good" initiatives and provide strategic direction on all matters related to AI and evidence-informed policy. Provide strategic and technical leadership to ensure high-quality work in portfolio research projects, policy publications, analysis, evidence presentations and reviews, and policy recommendations.

• Serve as the staff lead for Project AI Evidence (PAIE)
  • Oversee and manage the PAIE team, including overseeing PAIE RFPs/funding competitions to support cutting edge pilots and randomized controlled trials to advance scientific knowledge and actionable policy insights at the intersection of AI and global development.
  • Provide strategic and technical guidance to strengthen J-PAL’s AI research portfolio, including PAIE-funded projects, future RFPs, policy outputs, evidence reviews, and capacity-building efforts.
  • Advising PAIE staff and Faculty Co‑Chairs on the academic quality, coherence, and strategic direction of AI research opportunities.
  • Help researchers and partners distinguish between model development, algorithm evaluation, pilot testing, and downstream impact evaluation.
  • Provide strategic input on future PAIE RFP design, proposal review criteria, matchmaking strategy, and applicant guidance.
  • Advising J-PAL’s capacity‑building teams on how to incorporate AI for social good into trainings, government partnerships, and the development of training materials for researchers and policymakers.
  • Develop frameworks, playbooks, and evidence‑gap memos that help researchers and policymakers evaluate AI tools responsibly.
  • Contribute to J-PAL’s external thought leadership on AI for social good through articles, policy pieces, presentations, conferences, and other public‑facing outputs.

Build and…