Overview
The World Bank seeks an AI Engineer to design, develop, and deploy AI solutions within the Azure cloud environment, focusing on enhancing operational efficiency and knowledge management through intelligent agent systems.
Key Responsibilities
- Build and improve LLM-enabled features including prompt templates, structured outputs, tool/function calling, and logging.
- Design and implement agentic workflows with orchestrator–subagent patterns.
- Build and tune RAG pipelines and run evaluations for accuracy, task completion, latency, and safety.
- Integrate AI solutions with internal systems, APIs, and document repositories.
- Establish CI/CD pipelines for solutions deployment using Azure DevOps.
- Configure monitoring and observability using Azure Monitor, Application Insights, and custom logging.
- Ensure deployments comply with World Bank Group IT security policies, data classification requirements, and privacy standards.
- Implement Responsible AI guardrails, including content filtering, output validation, and human-in-the-loop escalation.
- Apply and mature reusable patterns and architectural standards for AI development.
- Produce technical documentation including architecture design documents, API specifications, deployment guides, and operational run-books.
- Develop governance documentation covering model cards, data lineage, risk assessments, and responsible AI checklists.
- Conduct knowledge transfer sessions with INT technical teams.
- Prepare user-facing guides and training materials for non-technical stakeholders.
Required Experience
Minimum 2 years of overall experience as an AI Engineer or in a similar role, with a successful track record of working with AI, ML, and LLMs. Within that, a minimum of 2 years of hands-on experience designing and developing AI solutions, with demonstrable experience in LLMs, RAG, and AI systems. Hands-on experience with LLM APIs, RAG, vector search, agent frameworks, tool/function calling, context engineering, and prompt design, plus LLM evaluation and observability. Proven experience building and deploying solutions on cloud. Experience taking AI solutions to production (CI/CD, containerization, monitoring). Data engineering or science experience. Experience working in international development, public sector, or multilateral organization contexts. Familiarity with World Bank operational policies, IT standards, or similar institutional environments. Experience with multi-agent system design and agentic workflow orchestration at scale.
Qualifications
Bachelor's degree in Computer Science, AI/ML, Data Science, Software Engineering, or a closely related field (preferred: Master's degree or higher in a relevant discipline).