AI Software Engineer Lead

Organizational Context

The Division of Business Operations (BOS) supports WHO in the European Region by providing services in HR, finance, procurement, ICT, and facilities management. The ICT Unit specifically focuses on implementing digital and technological solutions across the region, ensuring robust connectivity, advanced software, and data security to empower WHO's strategic goals.

Job Purpose

This role spearheads the implementation and advancement of AI and ML initiatives within WHO/Europe. It involves developing cutting-edge internal and external applications, guiding technical divisions on complex challenges, and promoting innovative digital solutions. The position requires leading AI/ML project definition, setting technical direction for data integration and automation, and overseeing the full AI project lifecycle from data acquisition to deployment and monitoring.

Responsibilities

Lead the definition and implementation of AI/ML initiatives in WHO/Europe, setting project priorities and work plans. Drive technical direction for data integration and AI-related automation, including real-time data ingestion and processing. Design, implement, and iterate on AI prototypes and scalable solutions. Oversee the end-to-end development cycle of AI projects, from data acquisition to deployment and monitoring. Guide the development of internal and external applications using modern frameworks, ensuring software engineering best practices. Develop and manage cloud-based solutions for AI/ML workloads, optimizing for performance and cost. Lead and mentor AI and software professionals, fostering innovation and ethical AI application. Collaborate with teams to integrate AI solutions, manage large datasets, and ensure model performance and accuracy.

Work Experience

A minimum of seven years of progressive experience is required. This includes software engineering and architecture, developing cloud-native applications, deploying AI models in the cloud, integrating generative AI, developing automated analytical pipelines, and managing complex applications with front-end stacks and databases.

Skills

Theoretical understanding of algorithms, data structures, and computational complexity. Proficient in AI/ML techniques, frameworks, and methodologies, including production deployment and monitoring. Strong proficiency in programming languages like Python, Java, or JavaScript/Node, and AI libraries/APIs. Experience with Azure AI solutions (Azure AI Search, indexers, skillsets). Solid understanding of DevOps, CI/CD, Docker, and Kubernetes. Data engineering skills for large datasets. Strong problem-solving abilities. Emotional intelligence and the ability to manage emotions and help others.

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