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E T Consultant 1 - AI Engineer
Software Engineering, Data Science · Contractor
Posted on Sep 21, 2026
At the World Bank, a member of the World Bank Group (WBG), you’ll join a diverse, global community working across cultures, disciplines, and borders to address the world’s most pressing development challenges. With 1.2 billion young people reaching working age in the decade ahead, the challenge of job creation has never been greater. Through partnerships across 145 countries and more than 182 offices worldwide, we work with governments, private sector, development partners and other stakeholders to invest in people, strengthen markets, and deliver scalable, data-driven solutions that generate more and better jobs and improve lives. For more information, visit https:// www.worldbank.org/en/who-we-are/ibrd Background INT is undergoing a significant transformation driven by the adoption of artificial intelligence to enhance operational efficiency, knowledge management, and decision-support capabilities across its global operations. As part of this strategic modernization agenda, the organization is seeking to deploy intelligent, autonomous AI agent systems capable of performing complex, multi-step tasks with minimal human intervention. INT operates on a Microsoft Azure cloud infrastructure (data storage, compute, identity, and AI/ML services) and leverages a Databricks platform for governed data and advanced analytics. AI solutions are expected to integrate cleanly with this stack and to follow established security, data-governance, and Responsible AI practices. AI agents represent a next-generation paradigm beyond traditional automation, enabling systems to reason, plan, use tools, and execute workflows dynamically. These capabilities are particularly relevant for internal functions such as procurement support, knowledge retrieval, document processing, policy compliance checking, and operational analytics. This engagement will contribute directly to INT’s digital transformation priorities, consistent with ongoing investments in data-driven tools and intelligent systems across the institution. This Terms of Reference (TOR) outlines the duties and responsibilities, deliverables and qualifications, for an AI Engineer to be engaged by the World Bank’s INT department to design, develop, and deploy AI solutions within the Azure cloud environment. This role reports to the INT Data Lab team lead and works closely with data scientists, data engineers, software engineers, and domain stakeholders. Specific milestones and priorities are agreed with the team lead and reviewed on a regular cadence. Duties and Responsibilities AI solutions Development • Build and improve LLM-enabled features: prompt templates, structured outputs, tool/function calling, and robust logging and error handling. • Design and implement agentic workflows (planning, tool use, memory, multi-step execution), including orchestrator–subagent patterns where appropriate. • Build and tune RAG pipelines (ingestion, chunking, metadata, embeddings, retrieval) and run evaluations for accuracy, task completion, latency, and safety. • Integrate AI solutions with INT's internal systems, APIs, and document repositories to deliver measurable operational value. AI solutions Deployment and Operations • Establish CI/CD pipelines for solutions deployment using Azure DevOps. • Configure monitoring and observability using Azure Monitor, Application Insights, and custom logging to track performance, errors, and usage patterns in production. • Ensure all 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 mechanisms where required. • Apply and help mature reusable patterns and architectural standards for AI development that are scalable, secure, and maintainable. Documentation Knowledge Transfer • Produce comprehensive 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 structured knowledge transfer sessions with INT technical teams to ensure sustainability of deployed solutions. • Prepare user-facing guides and training materials for non-technical stakeholders interacting with AI agent interfaces. Deliverables • Deployed AI solutions and prototypes — working prototypes and production-deployed LLM/agent solutions for prioritized use cases, integrated with INT systems on Azure and following team standards. • Optimized RAG pipelines — efficient indexing, retrieval, and inference, delivered as reusable agent/RAG components (ingestion steps, retrieval configs, tool integrations). • Prompt performance and evaluation reports — comparative analyses of prompt/model performance, with prompts iterated based on user feedback and metrics (accuracy, task completion, latency, safety). • CI/CD, monitoring, and resolved integrations — deployment pipelines, monitoring/alerting, and integration issues resolved in collaboration with developers and DevOps. • Technical documentation, version control, and change logs — architecture/API docs and runbooks, with AI model version control and change logs maintained and kept current. • Knowledge transfer and training materials — KT sessions for INT technical teams and user-facing guides for non-technical stakeholders.