Senior AI Systems Engineer at United Nations Environment Programme (UNEP)

Duties and Responsibilities

Senior Data Scientist to provide long-term leadership in AI systems development, there is an immediate operational need to:

• Implement and enhance priority AI use cases aligned with PoW indicators 7.1 and 7.2;
• Strengthen shared technical architecture supporting integration into the World Environment Situation Room;
• Establish operational monitoring, performance optimization, and governance safeguards for AI deployment;
• Support the assessment, design, and responsible deployment of AI tools in line with UNEP’s mandate to strengthen environmentally sustainable artificial intelligence practices.
• Ensure documentation and knowledge transfer to enable internal maintenance and scale-up; Engaging a Senior AI Systems Engineer (Consultant) for a six-month period will enable UNEP to maintain momentum in delivering tangible digital solutions under the Digital Transformations subprogramme, directly contributing to measurable progress under PoW 2026–2027 indicators, while ensuring continuity during the recruitment of the permanent P4 and P5 positions.
• This post is remotely located in Nairobi with the possibility of remote arrangements with several trips to Nairobi, and reports to the Chief Digital Officer .

Qualifications/special skills

• An advanced university degree (Master’s degree or equivalent) in Data Science, Computer Science, Artificial Intelligence, Machine Learning, Statistics, Engineering, Applied Mathematics, or a related quantitative field is required.
• A first-level university degree in combination with two additional years of qualifying experience may be accepted in lieu of the advanced degree.
• A minimum of seven (7) years of progressively responsible professional experience in data science, machine learning, artificial intelligence, or related technical fields is required.
• Experience in implementing large language model (LLM)-based applications, including retrieval-augmented generation (RAG) architectures, document processing pipelines, and knowledge-based AI systems, is highly desirable.
• Proven experience with: Cloud platforms (preferably Microsoft Azure, including Azure ML, Azure OpenAI, Azure AI Search or equivalent services); Data ingestion and orchestration tools; Vector databases and embedding-based retrieval systems; API-based system integration and backend services; Monitoring, logging, and performance optimization of AI systems in production environments; Implementing safeguards to mitigate hallucinations, prompt injection, and other AI-related risks is desireable
• Experience working with environmental, geospatial, or policy-related data is desireable Prior experience working within the United Nations system, international organizations, or similarly complex institutional environments is desirable