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• FAO is committed to achieving workforce diversity in terms of gender, nationality, background and culture.
• Qualified female applicants, qualified nationals of non-and under-represented Members and person with disabilities are encouraged to apply;
• Everyone who works for FAO is required to adhere to the highest standards of integrity and professional conduct, and to uphold FAO's values
• FAO, as a Specialized Agency of the United Nations, has a zero-tolerance policy for conduct that is incompatible with its status, objectives and mandate, including sexual exploitation and abuse, sexual harassment, abuse of authority and discrimination　　
• All selected candidates will undergo rigorous reference and background checks
• All applications will be treated with the strictest confidentiality

FAO’s commitment to environmental sustainability is integral to our strategic objectives and operations.

Organizational Setting

The FAO Regional office for Asia and the Pacific (FAO-RAP) support member countries in the development of knowledge products, capacity development and implementation of programmes and projects in food security, agriculture, rural development, natural resource management and agro-processing in developing countries and countries in transition, assisting governments and country stakeholders, main development partners, regional and national institutions with the policy and strategic planning to achieve food security and nutrition, make agriculture, forestry and fisheries more sustainable and productive, reduce rural poverty, make food value chains more efficient and inclusive and promote climate change adaptation and/or mitigation.

Under the FAO-RAP regional priority on “Accelerating sustainable natural resources management for biodiversity conservation and climate action,” FAO aims to support Members to protect, restore and promote sustainable use of terrestrial and aquatic ecosystems and combat climate change in realizing more efficient, inclusive, resilient and sustainable agri-food systems. With this priority FAO is implementing work programmes including actions to strengthen policy advice to Members for Agriculture, Forestry and Other Land Use (AFOLU) sectors engagement in 2030 Agenda processes to address climate change and foster multi-risk management, while also working closely with the Better Life – Emergencies pillar to ensure that anticipatory action, disaster risk reduction, and emergency response are effectively integrated into regional and national efforts. This joint approach helps countries not only to mitigate and adapt to climate risks, but also to prepare for and respond to crises in ways that protect livelihoods, enhance resilience, and reduce the impacts of disasters on food security and nutrition.

This work is coordinated regionally by the Climate Change, Resilience, Land and Water Module (CRLWM), which leads technical quality assurance and coherence of FAO’s field programme in Asia and the Pacific. Within this framework, the Specialist in Agrometeorology, Early Warning, and Artificial Intelligence (AI)/Machine Learning (ML) will contribute to the design, technical backstopping, and implementation of projects and knowledge products that strengthen the use of agro-climate information, AI-driven predictive analytics, and early warning systems for agricultural risk management and anticipatory action. The position may be home-based with travel required for field missions across the region.

Reporting Lines

The Specialist in Agrometeorology, Early Warning, and AI/ML will work under the overall technical supervision of the FAO Emergency and Rehabilitation Officer, in close collaboration with the FAO Representation in the relevant country/ies of assignment.

Technical Focus

This position focuses on advancing climate-resilient agriculture through the integration of agrometeorology, early warning systems, and AI/ML. The Specialist will apply specialized knowledge in agro-climatic forecasting, climate risk monitoring, and climate/crop interactions to strengthen disaster and climate change adaptation decision-making. They will design and optimize early warning models, harness AI/ML techniques for predictive analytics, and ensure that forecasts are actionable and accessible for farmers, governments, and humanitarian actors. The role emphasizes bridging science and practice by developing innovative, data-driven solutions that improve preparedness, reduce agricultural losses, and enhance climate resilience of vulnerable farmers under increasing climate risks. The work under the Specialist should also be done under CSI Agro-informatics guidance, following the One FAO Early Warning and Risk Monitoring approach.

Tasks and responsibilities

Technical agromet and early warning support

• Translate climate and weather forecasts into agricultural risk insights for crops, livestock, and fisheries.
• Develop agro-advisories and decision-support tools for farmers and policy makers.
• Design and strengthen early warning systems integrating climate, hydrological, and agricultural data.
• Define risk thresholds and trigger mechanisms for anticipatory action, and support strengthening of their monitoring systems, including automation of these.
• Ensure last-mile communication of warnings through user-friendly channels and formats.
• Train extension officers and communities on interpreting early warnings and applying agro-advisories.
• Contribute to technical reports on best practices, approaches and policies to increase the development of advanced climate services for agriculture.

Design and implement AI/ML tools to improve agromet and early warning systems

• Apply AI/ML models for predictive analytics and strengthen early warning systems in data-poor areas.
• Integrate multiple data sources (remote sensing, IoT, farmer registries, climate models) into ML pipelines.
• Test and validate models for accuracy, scalability, and operational use in decision-making.
• Build capacity of national meteorological agencies, agricultural ministries, and local institutions on agrometeorology and
AI-driven forecasting.
• Lead applied research and pilot initiatives linking agrometeorology, anticipatory action, and AI/ML innovations such as
agent-based advisors and digital twins.

Collaboration and project design

• Collaborate with governments, universities, research centers, and technology providers and users (e.g. insurance providers) on model development and validation.
• Pilot and scale innovative approaches such as mobile-based agro-advisory apps and automatization of anticipatory action triggers.
• Contribute to the formulation of GEF, GCF, and Adaptation Fund (AF) concept notes and full funding proposals.
• Perform other related duties as required.

CANDIDATES WILL BE ASSESSED AGAINST THE FOLLOWING

Minimum Requirements

• For Consultants\: Advanced university degree from an institution recognized by the International Association of Universities (IAU)/UNESCO in agrometeorology, climatology, meteorology, hydrology, data science or artificial intelligence. Consultants with a bachelor's degree need two additional years of relevant professional experience.
For PSAs\: University degree from an institution recognized by the International Association of Universities (IAU)/UNESCO in agrometeorology, climatology, meteorology, hydrology, data science or artificial intelligence.
• 1 year of relevant experience for Category C, 5 years of relevant experience for Category B, and 10 years of relevant experience for Category A in analytical studies, and/or in planning, design, supervision of meteorology and agrometeorology projects and programmes, including in developing countries and/or countries in transition.
• Working knowledge (level C) of English.

FAO Core Competencies

• Results Focus
• Teamwork
• Communication
• Building Effective Relationships
• Knowledge Sharing and Continuous Improvement

Technical/Functional Skills

• Extent and relevance of experience in designing and implementing agrometeorological and early warning systems for agriculture and food security.
• Extent and relevance of experience in applying AI/ML techniques to climate and agricultural datasets, including model development, testing, and validation.
• Extent and relevance of experience in conducting climate risk and vulnerability assessments and translating forecasts into actionable agro-advisories for farmers, governments, and development partners.
• Extent and relevance of experience in developing digital tools, platforms, or services that integrate climate, remote sensing, and agricultural data to support anticipatory action and disaster risk reduction.
• Extent and relevance of experience in preparing technical studies, knowledge products, or operational guidelines on agrometeorology, early warning, and AI/ML applications in agriculture.
• Extent and relevance of experience in strengthening institutional and community capacities to use climate information, early warning, and AI/ML-driven decision-support systems.
• Demonstrated ability to work with government agencies, national meteorological and hydrological services, agricultural institutions, and private sector partners to co-develop and apply forecasting and early warning solutions.
• Relevance of experience in developing countries and/or in Asia and the Pacific, particularly in applying agrometeorology and AI/ML to support climate resilience in agriculture.
• Working knowledge of Chinese, French, Spanish, Arabic or Russian seen as an asset, but not mandatory.

Please note that all candidates should adhere to FAO Values of Commitment to FAO, Respect for All and Integrity and Transparency

HOW TO APPLY

• To apply, visit the recruitment website at Jobs at FAO and complete your online profile. We strongly recommend that your profile is accurate, complete and includes your employment records, academic qualifications, and language skills
• Candidates are requested to attach a letter of motivation to the online profile
• Once your profile is completed, please apply, and submit your application

• Please note that FAO only considers higher educational qualifications obtained from an institution accredited/recognized in the World Higher Education Database (WHED), a list updated by the International Association of Universities (IAU) / United Nations Educational, Scientific and Cultural Organization (UNESCO). The list can be accessed at http\://www.whed.net/. These qualifications should be in alignment with the International Standard Classification of Education (ISCED) mappings.

• Candidates may be requested to provide performance assessments and authorization to conduct verification checks of past and present work, character, education, military and police records to ascertain any and all information which may be pertinent to the employment qualifications
• Incomplete applications will not be considered
• Personal information provided on your application may be shared within FAO and with other companies acting on FAO’s behalf to provide employment support services such as pre-screening of applications, assessment tests, background checks and other related services. You will be asked to provide your consent before submitting your application. You may withdraw consent at any time, by withdrawing your application, in such case FAO will no longer be able to consider your application
• Only applications received through the FAO recruitment portal will be considered
• Your application will be screened based on the information provided in your online profile
• We encourage applicants to submit the application well before the deadline date.

If you need help or have queries, please create a one-time registration with FAO’s client support team for further assistance\: https\://fao.service-now.com/csp

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