Innovation Specialist (AI-assisted Quality Assurance)

Job Posting Organization:
The Food and Agriculture Organization of the United Nations (FAO) is a specialized agency of the United Nations that leads international efforts to defeat hunger. Established in 1945, FAO has a mission to help eliminate hunger, food insecurity, and malnutrition; make agriculture, forestry, and fisheries more productive and sustainable; reduce rural poverty; and enable inclusive and efficient agricultural and food systems. With over 194 member countries, FAO operates in more than 130 countries worldwide, employing thousands of professionals dedicated to improving security" style="border-bottom: 1px dotted #007bff !important;">security" style="border-bottom: 1px dotted #007bff !important;">food security and nutrition, promoting sustainable agriculture, and enhancing the resilience of livelihoods in the face of crises.

Job Overview:
The Innovation Specialist (AI-assisted Quality Assurance) will play a crucial role in the Office of Innovation (OIN) at FAO, specifically within the Agrifood Systems Technologies and Innovations Outlook (ATIO) initiative. This position is designed for an individual who will contribute both conceptually and technically to the development and implementation of automated testing and AI-assisted quality assurance protocols. The incumbent will work closely with the ATIO technical team to ensure the reliability and integrity of data pipelines and Knowledge Base content. The role requires a strong understanding of quality assurance mechanisms, particularly in the context of data-intensive platforms, and the ability to operationalize AI-assisted QA protocols to enhance the performance of the Knowledge Base and STI portal.

Duties and Responsibilities:
The incumbent will be responsible for a variety of tasks, including: establishing the ATIO Knowledge Base QA mechanism, developing QA indicators, and integrating technical experts into validation processes. They will design and implement automated test frameworks for various features of the Knowledge Base, operationalize AI-assisted QA protocols, and support the establishment of CI/CD-driven QA gates. The role also involves implementing performance tracking systems, ensuring data governance compliance, collaborating with product and content teams, supporting incident response processes, and developing core functionalities related to natural-language interaction. Additionally, the incumbent will contribute to the assessment of existing FAO and non-FAO tools and prepare documentation for the ATIO Knowledge Base QA protocol.

Required Qualifications:
Candidates must meet the following minimum requirements: for consultants, an advanced university degree in Computer Science, Software Engineering, Data Science, or a related field is required; those with a bachelor's degree must have two additional years of relevant experience. For PSAs, a relevant technical degree or certificate is necessary. Additionally, candidates should have at least two years of relevant experience in software quality assurance, software engineering, or data engineering, with a focus on QA automation for data-intensive platforms. Experience with AI, machine learning, or natural language processing techniques for content validation is also required, along with a working knowledge of English and limited knowledge of one of the other FAO official languages.

Educational Background:
The educational background required for this position includes an advanced university degree from an institution recognized by the International Association of Universities (IAU)/UNESCO in fields such as Computer Science, Software Engineering, Data Science, or a related area. For those applying as PSAs, a relevant technical degree or certificate is sufficient. Candidates with a bachelor's degree must have additional professional experience to qualify.

Experience:
The position requires a minimum of two years of relevant experience in software quality assurance, software engineering, data engineering, or related technical areas. This experience should include a focus on QA automation for data-intensive platforms, such as web applications, APIs, and data pipelines. Candidates should also have experience applying AI, machine learning, or natural language processing techniques for content validation and metadata checks.

Languages:
A working knowledge (Level C) of English is mandatory, along with a limited knowledge (Level B) of one of the other FAO official languages, which include French, Spanish, Arabic, Chinese, or Russian. For PSA.SBS positions, a working knowledge of English is sufficient.

Additional Notes:
This position is likely to be full-time and may involve international collaboration, given FAO's global presence. The role is critical for ensuring the quality and reliability of the data systems that support FAO's mission. Compensation and benefits will be aligned with FAO's standards for similar positions, and candidates may be assessed based on their ability to work in multi-stakeholder environments and their experience in developing documentation and protocols for technical systems.