Agriculture Program Lead, The AI Access Initiative

Evidence Action

2h•$155,000 - $170,000•Remote

About The Position

The AI Access Initiative, incubated at Evidence Action, is launching to scale AI-enabled 'big bets' to benefit people in poverty in low- and middle-income countries (LMICs). The organization aims to operate at the intersection of global development actors, AI labs, and researchers to drive meaningful access to AI benefits for those living in poverty. It will create open-sourced resources like playbooks and toolkits to guide the design and launch of impactful AI programs. Initially, the initiative will focus on scaling programs in Agriculture and Health. The organization is led by experienced individuals in AI and global development and builds on Evidence Action's track record of reaching over 530 million people with evidence-based programs. The initiative's approach involves scaling 'big bet' AI interventions, such as AI-enabled forecasts for farmers and improved medical diagnosis, and partnering with governments to create an enabling environment for 'AI for Good' ecosystems. They are advancing high-scoring interventions through rigorous vetting processes and are currently conducting deeper analysis on global health opportunities.

Requirements

5+ years' experience as a builder in international development, with a strong preference for direct experience in agriculture, weather forecasting, smallholder advisory services, agricultural extension, value chain interventions, or rural last-mile delivery.
A proven track record of significantly scaling organizations and/or programs to deliver last-mile impact at the farmer level.
Training or early career experience in a high-rigor environment (e.g., top-tier management consulting, high-growth NGO program leadership, strategy/econ research) and the ability to rapidly get up to speed in new technical areas including AI/ML forecasting concepts.
Demonstrated success leading agriculture or rural development programs from idea to scaled delivery, including managing multi-stakeholder coalitions with governments, research institutions, NGO implementers, and private sector partners.
A track record as a strong people manager and builder: able to set clear standards, empower others, and cultivate a high-performance culture across distributed and field-based teams.
Experience working with Asian and/or African governments to drive large-scale change, with a strong preference for direct experience working with Indian state governments, ministries of agriculture, or national meteorological agencies.
High EQ and the ability to influence across diverse partners, from AI/forecasting researchers to frontline delivery staff to senior government officials.
Strong fluency with AI tools, and eager to experiment, learn, and adapt to emerging technologies.
Comfort with ambiguity and fast iteration; can define and test hypotheses, adapt quickly, and maintain focus on impact.
Excellent written and verbal communication skills; able to synthesize complex technical ideas into crisp narratives for different audiences.
Willingness and ability to travel extensively internationally (~20-40%), with significant time expected in India and other priority geographies.
Passion for the mission of ensuring that the benefits of frontier AI reach the world's poorest populations, while mitigating its downside risks.
Applicants must be legally authorized to work in the U.S. for roles based in the U.S.

Nice To Haves

Potential to expand into adjacent agriculture interventions over time.

Responsibilities

Own and lead the Agriculture program strategy: Set the multi-year vision and annual workplan to reach tens of millions of smallholder farmers with high-quality, AI-enabled forecasts and advisory services.
Drive state and national government partnerships: Build trusted relationships with ministries of agriculture, state-level governments, and meteorological agencies to enable forecast dissemination at scale, with a focus on institutionalization over time.
Manage delivery partner relationships: Coordinate with implementing partners and research collaborators to ensure forecasts are delivered cost-effectively and at high quality.
Design and oversee scaling pilots: Launch and evaluate work across new dissemination channels (SMS, WhatsApp, radio, telco partnerships) and new forecast types (e.g., dryspell, short-run), with rigorous learning agendas.
Translate across stakeholders: Serve as an effective bridge among forecasting researchers, AI labs, NGOs, funders, and government counterparts; communicate technical concepts crisply to non-technical audiences.
Build and lead the agriculture team: Recruit, coach, and manage country leads, state-level staff, and partner teams; cultivate a high-performance, high-accountability culture.
Drive learning and quality: Embed measurement, feedback loops, and cost-effectiveness analysis into the program; partner with M&E researchers to build the evidence base over time.
Operate in ambiguity: Chart paths forward in new geographies and problem spaces with urgency, rigor, and pragmatism.