Senior AI Engineer

The Organisation for Economic Co-operation and Development ( OECD ) is an international organisation comprised of 38 member countries, that works to build better policies for better lives. Our mission is to promote policies that will improve the economic and social well-being of people around the world. Together with governments, policy makers and citizens, we work on establishing evidence-based international standards, and finding solutions to a range of social, economic and environmental challenges. From improving economic performance and creating jobs to fostering strong education and fighting international tax evasion, we provide a unique forum and knowledge hub for data and analysis, exchange of experiences, best-practice sharing, and advice on public policies and international standard-setting.

The Executive Directorate (EXD) stewards OECD resources on behalf of the Secretary-General, with responsibility for people and wellbeing, budget management, security, infrastructure, and the OECD’s convening activities. EXD provides corporate services and strategic advice on management and corporate policies to the Secretary-General, Council and Standing Committees, and delivers compliance and risk management functions within its remit, operating in a fast-paced environment focused on management excellence.

Within the Executive Directorate (EXD), the Digital, Knowledge and Information Service (DKI) is responsible for overseeing corporate IT infrastructure and operations, maintaining digital security, information management, and delivering digital and other IT-related products and services. EXD/DKI also supports the safe adoption of artificial intelligence (AI) technologies across the Organisation.

Following the recommendation of the OECD AI Task Force and in line with the evolving AI-related requirements of the OECD, the CAI division has been established to support the safe adoption of AI technologies across the Organisation. CAI is tasked with overseeing the shift from initial experimentation towards the scaled adoption of AI (from Exploration to Institutionalisation) that delivers tangible value with a clear emphasis on enhancing organisational impact, improving productivity, and transforming ways of working.

In this role, you will sit within the AI Lab in EXD/DKI/CAIO. The AI Lab supports the development and operationalisation of the OECD’s corporate AI framework by identifying, designing and implementing high-value AI solutions that strengthen the Organisation’s analytical and operational capabilities.

You will be focused on building, structuring and industrialising AI solutions to support the Organisation’s adoption of advanced AI capabilities. You will also contribute to the development of internal AI capabilities.

Main Responsibilities

Design and Implement an Internal AI Engineering Framework

Build and Implement AI Solutions

- Contribute directly to the design, development and testing of AI applications, including:

- Prototyping and rapid iteration

- Implementation of RAG pipelines, agents and AI services

- Integration with enterprise systems and data sources

- Collaborate with internal teams to refine technical requirements and ensure solutions are feasible, robust and aligned with enterprise constraints.

- Select and apply appropriate technologies, including commercial AI platforms and open-source/open-weight models, depending on the use case.

Industrialise and Operationalise AI Use Cases

- Transform proofs of concept (PoCs) and experimental solutions into production-ready tools.

- Ensure solutions meet enterprise requirements in terms of:

- Performance and scalability

- Security and compliance

- Maintainability and supportability

- Financial sustainability

- Contribute to deployment, packaging and release processes.

- Support handover to operational teams, including documentation, knowledge transfer and alignment with support models.

- Develop reusable assets and components to accelerate future implementations.

Continuous Improvement

- Keep abreast of advances on emerging industry trends, related technologies, methodologies and best practices.

- Promote excellence and contribute to improving effectiveness, efficiency and division-level excellence.

- Contribute to other related tasks within EXD/DKI, as required.

Ideal Candidate Profile

Academic Background

Professional Background

- Hands-on engineering mindset and attention to technical quality.

- Ability to work autonomously on complex technical topics.

- Pragmatic, solution-oriented and delivery-focused approach.

- Strong problem-solving skills and adaptability in a fast-evolving field.

- Experience in international or multilateral environments is highly desirable.

The successful candidate would demonstrate/possess several of the following

Languages

- Fluency in one of the two OECD official languages (English and French) and knowledge of the other, with a commitment to reach a good working level.

Responsibilities

Design and develop a reusable framework for agentic AI solutions to be used across the Organisation.; Define and implement:; Reference architectures for AI and agent-based systems; Reusable components, libraries and templates; Standard patterns for orchestration, tool usage, memory and workflows; Produce technical documentation, guidelines and best practices to support consistent and scalable AI development.; Evaluate and integrate relevant tools, frameworks and approaches in a rapidly evolving ecosystem.

Requirements

Advanced university degree in Artificial Intelligence, Data Science, Computer Science, Economics, Public Policy or a related field, or equivalent practical experience.; Generative AI and Agentic Systems; Hands-on experience with Generative AI technologies, including LLMs, embeddings, Retrieval-Augmented Generation (RAG), and prompt engineering.; Proven experience building agent-based or multi-step AI systems, including orchestration, tool/function calling, and workflow design.; Ability to design efficient and reliable AI pipelines with attention to performance, latency and cost.; AI Platforms and Model Ecosystems; Practical experience with at least one major GenAI platform (e.g. OpenAI, Azure OpenAI, Anthropic, Google Vertex AI/Gemini, Mistral).; Experience integrating AI services into existing applications and enterprise environments.; Good understanding of trade-offs between different model providers and approaches.; Open-Source and Open-Weight Models; Hands-on experience with open-weight models and open-source AI stacks.; Experience with model deployment and optimisation techniques, such as fine-tuning (e.g. LoRA/PEFT), quantisation and model serving.; Ability to implement on-premises or hybrid AI solutions where required.; Software and Data Engineering; Strong programming skills in Python, with experience building production-grade applications.; Experience developing APIs, services and pipelines integrating AI components.; Familiarity with:; Vector databases and embedding pipelines; Indexing and retrieval strategies; Structured and unstructured data processing; Solid engineering practices (testing, version control, CI/CD, monitoring).; AI Platform Engineering; Experience contributing to the setup or operation of AI platforms or shared AI services.; Understanding of:; Authentication and access control; API management; Scalability and usage monitoring; Ability to contribute to secure and controlled AI service provisioning.; Security and Responsible AI; Understanding of risks related to AI systems, including data leakage, hallucinations and prompt injection.; Experience implementing technical safeguards, such as filtering, guardrails and secure design patterns.; Ability to operate within enterprise security and governance constraints.; OECD staff are expected to demonstrate behaviours aligned to six core competencies which will be assessed as part of this hiring process: Vision and Strategy (Level 1), Enable People (Level 1), Ethics and Integrity (Level 2), Collaboration and Horizontality (Level 2), Achieve Results (Level 2), Innovate and Embrace Change (Level 2).; To learn more about the definitions for each competency for levels 1-3, please refer to OECD Core Competencies .