Senior AI Architect

Senior AI Architect

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

ITS Vice Presidency Context

The Information and Technology Solutions (ITS) Vice Presidential Unit (VPU) enables the World Bank Group to achieve its mission of ending extreme poverty and boost shared prosperity on a livable planet by delivering transformative information and technologies to its staff working in over 150+ locations. For more information on ITS, see this video: https://www.youtube.com/watch?reload=9&v=VTFGffa1Y7w

Unit Context

The ITS Operations Products unit (ITSOP) enables the Bank's business processes through modern, flexible, and user-friendly digital platforms that integrate and optimize critical functions for front-line staff. ITSOP also drives AI-powered business solutions that support operational priorities and accelerate trusted, data-informed decision-making.

ITSOP is seeking an Associate Senior AI Solution Architect to lead the unit’s AI strategy and translate it into secure, scalable, and production-ready solutions. The successful candidate will personally design and prototype AI components, develop reference implementations, evaluate technical approaches, and guide engineering teams through deployment and operationalization. This is not a purely advisory role. It requires recent, demonstrable experience building and operating Generative AI and agentic solutions in enterprise environments.

Key Responsibilities

• AI Strategy and Architecture

• Develop the ITSOP AI strategy, capability roadmap, reference architectures, standards, and reusable patterns, aligned with enterprise direction and measurable operational outcomes.

• Translate business opportunities into prioritized AI use cases, target architectures, delivery approaches, and investment recommendations.

• Design end-to-end solutions spanning user experience, agents, models, retrieval, enterprise data, APIs, identity, security, observability, and operational support.

• Evaluate technology choices and architecture trade-offs across models, platforms, orchestration frameworks, retrieval approaches, and integration patterns.

• Hands-on Prototyping and Engineering

• Design, code, test, and demonstrate working prototypes and reference implementations using Python and modern software engineering practices.

• Graduate selected solutions from discovery and proof of concept through technical validation, production design, deployment, and operational readiness.

• Create reusable SDKs, templates, components, and implementation guidance that enable delivery teams to build consistently and securely.

• Conduct design and code reviews, troubleshoot complex cross-layer issues, and provide practical technical direction to engineering teams.

• Agentic AI, Enterprise Knowledge, and Integration

• Design and implement agentic solutions using tool calling, structured outputs, orchestration, state and memory management, routing, retries, fallbacks, and human approval patterns.

• Design safe single-agent and multi-agent workflows with clear task boundaries, controlled permissions, escalation paths, and failure handling.

• Build Retrieval-Augmented Generation and enterprise knowledge solutions using semantic search, vector retrieval, knowledge graphs, ontologies, and structured and unstructured data.

• Integrate agents with enterprise applications, APIs, event-driven services, data platforms, content repositories, and business workflows.

• Apply open agent interoperability approaches such as Model Context Protocol (MCP), Agent2Agent (A2A), or equivalent standards where appropriate.

• Production Quality, Security, and AI Operations

• Define and implement evaluation frameworks covering groundedness, relevance, completeness, task success, safety, latency, reliability, and cost.

• Create automated regression tests, representative evaluation datasets, and human-review processes for prompts, retrieval, tools, models, and agent behavior.

• Implement end-to-end tracing, prompt and configuration versioning, model and tool telemetry, cost monitoring, feedback capture, release controls, and rollback approaches.

• Apply AI-specific security controls for prompt injection, data leakage, unsafe tool execution, sensitive information, identity, authorization, auditability, and workload isolation.

• Embed Responsible AI, privacy, records management, compliance, and human oversight requirements throughout the solution lifecycle.

• Technical Leadership and Adoption

• Act as a trusted technical advisor while remaining directly involved in prototyping, implementation decisions, and production problem-solving.

• Partner with business, product, architecture, data, security, platform, and engineering teams to deliver measurable value and sustainable adoption.

• Mentor architects and engineers, share implementation practices, and raise the unit’s capability to deliver governed AI solutions.

• Monitor emerging AI technologies and recommend adoption only where they provide clear business, engineering, or operational value.

• Selection Criteria

• Master's degree in Computer Science, Software Engineering, Data Science, Artificial Intelligence/Machine Learning, Information Systems, or a related field, with a minimum of 8 years of relevant professional experience; or Bachelor's degree with a minimum of 10 years of relevant professional experience; or an equivalent combination of education and experience.

• Demonstrated experience designing, developing, deploying, and supporting enterprise-scale Generative AI and/or Agentic AI solutions in production environments.

• Proven experience translating business requirements into scalable technology solutions and delivering measurable business outcomes.

• Experience working with enterprise data, APIs, applications, workflow platforms, and knowledge management systems.

• Strong software engineering skills, including Python development and modern software delivery practices.

• Experience with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), agent frameworks, and AI solution architecture.

• Experience designing and implementing AI-enabled search, retrieval, document intelligence, and knowledge-grounded solutions.

• Knowledge of responsible AI principles, including security, privacy, governance, compliance, explainability, and risk management considerations.

• Demonstrated ability to communicate complex technical concepts and architectural decisions to both technical and non-technical stakeholders.

• Strong analytical, problem-solving, collaboration, and stakeholder management skills, with the ability to work effectively across multidisciplinary and globally distributed teams.

• Proven client focus, sound judgment, and commitment to delivering practical and measurable business outcomes.

• Demonstrated experience designing, implementing, operating, and continuously improving enterprise AI solutions in production environments across the full solution lifecycle.

• Preferred Qualifications

• Experience with enterprise AI platforms such as Azure OpenAI, AWS Bedrock, Azure AI Foundry, Microsoft Copilot Studio, Databricks Mosaic AI, or similar technologies.

• Experience implementing AI solutions within regulated or security-conscious environments.

• Experience developing reusable frameworks, reference architectures, standards, templates, or developer enablement assets.

• Relevant AI, cloud, architecture, security, or DevOps certifications.

• Experience designing knowledge-grounded AI solutions and reusable enterprise AI capabilities that support knowledge-intensive business processes, decision-making, and the safe, scalable adoption of AI.

As the World Bank Group continues to evolve, we value candidates who:

• Demonstrate the ability to