AI Solutions Analyst

World Bank Group • Washington, DC

4d • Onsite

About The Position

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. The ITS Data Office is the central entity within the World Bank Group’s Information and Technology Solutions (ITS) department responsible for enabling data, AI, information, and knowledge capabilities across the institution. The Platforms & Tools unit (ITSAI) is responsible for building, integrating, and continuously modernizing the foundational technology infrastructure that powers data, AI, archives, and knowledge services across the World Bank Group. ITSAI unit is seeking a motivated and high-potential early-career professional to contribute to the design, development, and operation of next-generation AI-enabled platforms and services. The selected candidate will contribute to building AI-driven solutions using foundational models and agentic AI approaches, working across AI Engineering & Platform Engineering disciplines to deliver secure, scalable, and impactful AI capabilities that address real-world development challenges. This role is ideal for early-career professionals who are passionate about applying AI to solve meaningful problems and are eager to learn and grow in a fast-paced, mission-driven environment.

Requirements

• Bachelor’s or Master’s degree with 2 years of experience or equivalent combination of education and experience (for example, in the IT field: Bachelor’s Degree with a minimum of 1 year of related work experience).
• Demonstrated exposure to AI/ML, cloud computing, or DevOps practices, with a clear interest in building scalable, production-ready systems
• Proficiency in at least one programming language (e.g., Python, Node.js, Go or similar), with a solid foundation in software engineering, cloud architecture, and modern development practices (Git, APIs)
• Working knowledge of cloud platforms (Azure, AWS, GCP), including automation, CI/CD pipelines, containerization, and infrastructure-as-code
• Understanding of API design, API Management (APIM), API gateways, and API security, including OAuth 2.0, OpenID Connect (OIDC), and identity solutions such as Azure Entra ID
• Familiarity with AI Gateway concepts, token consumption models, and observability tools for troubleshooting and performance monitoring
• Demonstrated interest and working knowledge in Artificial Intelligence, including Generative AI, Large Language Models (LLMs), machine learning, and Natural Language Processing (NLP)
• Experience or exposure to automation, platform engineering, and scalable system design, with awareness of microservices architecture and deep learning concepts
• Strong analytical, problem-solving, and critical thinking skills, with the ability to quickly learn and adapt in fast-paced technical environments
• Effective communication and collaboration skills, with a curiosity-driven mindset and commitment to continuous learning and innovation

Nice To Haves

• Microsoft Azure Fundamentals (AZ-900) or AWS Certified Cloud Practitioner
• Azure AI Fundamentals (AI-900) or equivalent
• Kubernetes or Docker introductory certifications
• Any entry-level certification in AI Engineering, DevOps or Cloud Engineering

Responsibilities

• Build AI-powered solutions leveraging hyper-scaler foundational AI services (e.g., Azure OpenAI, AWS Bedrock, Google Vertex AI managed AI/ML platforms)
• Apply foundation models and agentic AI patterns to solve real-world development challenges across World Bank business domains
• Implement sandboxed environments to safely test and evaluate AI agents before production deployment
• Ensure agents operate within controlled boundaries, including restricted tool access, data scope, and execution limits
• Contribute to building AI agent frameworks, SDKs, and reusable components enabling rapid solution development
• Assist in the design, fine-tuning, and evaluation of machine learning models & SLMs via MLOps.
• Support experimentation workflows for context engineering, model evaluation, and iterative improvements
• Contribute to responsible AI practices, including safety, explainability, and governance
• Help operationalize AI solutions using CI/CD deployment pipelines and runtime environments
• Leverage agent orchestration and agent harness patterns to safely deploy AI use cases in production
• Participate in designing APIs and services that expose AI capabilities to business applications
• Support observability through AI system monitoring, feedback loops, and performance insights
• Work under guidance of senior engineers while progressively building independence and technical depth
• Gain exposure to enterprise-scale AI applications and real-world development impact
• Support development, testing, and deployment of AI/ML models and platform components.
• Assist in building and enhancing internal AI platforms and self-service capabilities
• Implement and support monitoring, observability, and operational reliability practices
• Collaborate with cross-functional teams and contribute to agile development processes
• Enable delivery of self-service production-grade AI/ML solutions through robust engineering practices
• Develop Agentic AI Core & Foundational guard rails to enable AI at scale.
• Experiment with AI industry trends and assess feasibility, & viability.
• Leverage modern Agent Harness to safely deploy Agentic AI use cases in production.
• Build foundational expertise across AI, DevSecOps, and platform engineering domains

Benefits

• retirement plan
• medical, life and disability insurance
• paid leave, including parental leave
• reasonable accommodations for individuals with disabilities

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level