E T Consultant 1 – AI Engineer

World Bank Group•Washington, DC

6d•Onsite

About The Position

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. The World Bank is seeking an AI Engineer 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. The World Bank 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 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.

Requirements

Bachelor's degree in Computer Science, AI/ML, Data Science, Software Engineering, or a closely related field.
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 (e.g., LangGraph, AutoGen, Semantic Kernel, CrewAI, LlamaIndex, etc.), tool/function calling, context engineering, and prompt design, plus LLM evaluation and observability (evals, tracing, monitoring).
Strong in Python (preferred) or other programming languages, and API development (e.g., FastAPI).
Strong Responsible AI and security awareness (guardrails, data privacy, access control).
Proven experience building and deploying solutions on cloud (preferred: Azure).
Fluent, disciplined use of AI coding assistants.
Strong analytical and problem-solving skills with the ability to translate complex technical concepts for non-technical audiences.
Demonstrated ability to work independently and manage multiple priorities in a fast-paced environment.
Collaborative mindset with experience working in cross-functional teams.
Excellent written and verbal communication skills in English.

Nice To Haves

Master's degree or higher in a relevant discipline.
Microsoft Azure certifications (e.g., Azure AI Engineer Associate — AI-102) are highly desirable.
Experience taking AI solutions to production (CI/CD, containerization, monitoring).
Data engineering or science experience (Databricks, vector or Graph databases).
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.

Responsibilities

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.
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.
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.