Overview
The AI Solutions Architect (Business Engagement) role supports the safe adoption of AI technologies across the Organisation by identifying, designing, and implementing high-value AI solutions. This role acts as the principal interface between the AI Lab and OECD Directorates to identify AI opportunities and translate them into structured use cases.
Key Responsibilities
- Identify and prioritise AI opportunities by working with Directorates to identify high-value tasks and business processes that could benefit from AI, and evaluate opportunities according to organisational impact, scalability, feasibility and strategic value.
- Translate business needs into structured AI workflows and solution designs, and identify the most appropriate AI architecture for each use case.
- Develop proofs of concept and pilot solutions using appropriate AI tools and platforms, and contribute to coding, prompt engineering, API integration, workflow design and evaluation.
- Analyse existing business processes and identify organisational and technical bottlenecks.
- Represent the OECD in international AI fora, partnerships and policy discussions, and build and maintain strategic relationships with governments, international organisations, academia and the private sector.
- Keep abreast of advances on emerging industry trends, related technologies, methodologies and best practices.
Required Experience
- Demonstrated ability to identify, scope and structure AI use cases.
- Demonstrated prompt engineering and context engineering skills.
- Understanding of AI workflow design and evaluation.
- Understanding of the strengths and limitations of proprietary and open-weight models.
- Familiarity with cloud-based and on-premises deployment models.
- Ability to assess architectural trade-offs relating to security, cost, scalability and governance.
- Strong analytical and communication skills, with the ability to translate business requirements into technical solutions.
- Experience in international or multilateral environments is highly desirable.
- Experience building applications using APIs and Python.
- Strong experience with at least one leading AI platform (OpenAI, Microsoft, Anthropic, Mistral or Google).
- Familiarity with orchestration frameworks, retrieval-augmented generation (RAG), agents and workflow automation would be an advantage.
Qualifications
Advanced university degree in Artificial Intelligence, Data Science, Computer Science, Economics, Public Policy or a related field, or equivalent practical experience.
