Senior AI Engineer

The Senior AI Engineer will design, develop, and industrialise AI solutions to support the OECD's adoption of advanced AI capabilities. The role involves building reusable AI frameworks, integrating AI tools, and operationalising AI use cases to enhance organisational impact and productivity.

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.
• Develop reusable components, libraries and templates.
• Establish 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.
• Contribute directly to the design, development and testing of AI applications including prototyping, rapid iteration, implementation of RAG pipelines, agents and AI services.
• Integrate AI solutions 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.
• Transform proofs of concept and experimental solutions into production-ready tools.
• Ensure solutions meet enterprise requirements in terms of performance, scalability, security, compliance, maintainability, supportability and 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.
• 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.

Requirements

• Advanced university degree in Artificial Intelligence, Data Science, Computer Science, Economics, Public Policy or a related field, or equivalent practical experience.
• 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.
• 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.
• 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.
• 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.
• 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.
• Familiarity with indexing and retrieval strategies.
• Familiarity with structured and unstructured data processing.
• Solid engineering practices (testing, version control, CI/CD, monitoring).
• Experience contributing to the setup or operation of AI platforms or shared AI services.
• Understanding of authentication and access control.
• Understanding of API management.
• Understanding of scalability and usage monitoring.
• Ability to contribute to secure and controlled AI service provisioning.
• 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.
• 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.

Skills

• Artificial Intelligence
• Data Science
• Generative AI
• Large Language Models
• Prompt Engineering
• Retrieval-Augmented Generation
• Agent-Based AI Systems
• AI Workflow Tools
• AI Pipeline Design
• GenAI Platforms
• OpenAI
• Azure OpenAI
• Anthropic
• Google Vertex AI
• Mistral
• AI Integration
• Open-weight Models
• Open-source AI
• Model Deployment
• Model fine-tuning
• LoRa
• PEFT
• Model Quantisation
• Model Serving
• On-premises AI Solutions
• Hybrid AI Solutions
• Python Programming
• API Development
• AI Services
• Vector Databases
• Embedding Pipelines
• Indexing Strategies
• Data Retrieval Services
• Structured Data Processing
• Unstructured Data Processing
• Software Testing
• Version Control Systems
• CI/CD
• Monitoring
• AI Platform Operation
• Authentication
• Access Control
• API Management
• Scalability considerations
• Usage Monitoring
• AI Security
• Data Leakage Prevention
• Hallucination Mitigation
• Prompt Injection Prevention
• Technical Safeguards
• Filtering
• Guardrails
• Secure Design Patterns
• Enterprise Security Design
• Governance Constraints

Languages

English, French