Senior IT Officer, Business Solutions I

**Senior IT Officer, Business Solutions I (AI Solutions Officer - Knowledge)**

**Job #**:

- req34645

**Organization**:

- World Bank

**Sector**:

- Information Technology

**Grade**:

- GG

**Term Duration**:

- 2 years 0 months

**Recruitment Type**:

- Local Recruitment

**Location**:

- Singapore, Washington, DC, Sofia, Bulgaria

**Required Language(s)**:

- English

**Preferred Language(s)**:
**Closing Date**:

- 11/28/2025 (MM/DD/YYYY) at 11:59pm UTC

**Description**

Background & General Description

The Information and Technology Solutions (ITS) Vice Presidential Unit supports the World Bank Group’s mission by delivering transformative digital solutions to staff across 150+ global locations. Within ITS, the Operations Effectiveness unit (ITSEF), part of the Operations & Country Engagement Solutions department (ITSOE) department, leads efforts to enhance operational efficiency and data-driven decision-making in Bank’s Operations.

The Senior AI Solutions Engineer will:

Team Leadership: Manage and mentor a team of AI engineers and data scientists, ensuring delivery of high-quality AI solutions.
- Research & Innovation: Stay abreast of the latest AI/ML advancements, incorporating innovative techniques (e.g., retrieval-augmented generation, agentic frameworks, reinforcement learning) into enterprise products and to support sector specific solutions
- Collaboration: Work closely with product managers, solution architects, and cross-functional teams to integrate AI solutions into enterprise systems and workflows.
- Performance Monitoring: Establish success metrics, continuously monitor AI models, and optimize for accuracy, efficiency, and reliability.
- Documentation & Reporting: Produce architectural blueprints, technical documentation, and progress reports for internal and external stakeholders.
- AI Governance & Security: Ensure solutions meet enterprise standards for data privacy, ethics, and responsible AI use.**Selection Criteria**
- Advanced degree (Master’s) with 8+ years, or Bachelor’s with 10+ years, in Computer Science, Data Science, Engineering, or related field—or equivalent combination of education and experience.
Proven ability to design end-to-end AI solution architectures and develop technical roadmaps, aligning emerging technologies (LLMs, RAG, knowledge graphs, multi-agent systems) with enterprise standards and long-term sectoral priorities.**Technical Expertise**
- AI Agents: Experience with frameworks like LangGraph, CrewAI, or similar; demonstrable expertise in building autonomous multi-step AI agents.
- Generative AI & NLP: Expert-level knowledge of LLMs, generative models, and NLP (e.g., Hugging Face, spaCy, NLTK).
- RAG & Search: Experience implementing retrieval-augmented generation using Azure AI Search, AWS OpenSearch, GCP Vertex AI, and vector DBs (e.g., Pinecone, Weaviate). Implement feedback loops to improve retrieval quality (click/usage signals, human-in-the-loop labeling, relevance tuning).
- Data Engineering: Skilled in building pipelines with Databricks, Azure Data Factory, or similar.
- Programming & MLOps: Strong Python skills; experience in CI/CD, containerization (Docker, Kubernetes), and microservices deployment.
- AI Infrastructure: Cloud deployment expertise (Azure, AWS, GCP); scaling and monitoring AI services.
- Reinforcement Learning: Practical experience in RL for decision-making and predictive modeling.
- Experimentation & Evaluation - Test and evaluate new LLMs, emerging AI technologies, and frameworks to identify opportunities for innovation.
- Guardrail Development - Develop and engineer the implement safeguards to ensure AI responses are accurate, secure, and aligned with ethical guidelines.
- Responsible for observability AI Workloads: Prompt/response stores, evaluation harnesses, and observability products (e.g. LangSmith, Kibana) to monitor hallucinations, guardrail triggers, and RAG quality.
- Optimization & Security: Experience with model pruning, quantization, knowledge distillation, and AI security (adversarial defense, privacy).
- AI Ethics & Fairness: Familiarity with bias detection, explainability, and fairness frameworks. Implement guardrails and policy enforcement (content filters, safety classifiers, red teaming, jailbreak prevention)
- Responsible for prompt design frameworks, agent traceability, user personalization, and feedback
- loop design.

Desired Qualifications (Strong Plus)
- Experience with edge AI (SLMs on devices).
- Demonstrated expertise in AI interpretability and explainability.
- Relevant certifications: Azure AI Engineer Associate, Google ML Engineer, SAFe for DevOps/Architects, AI Ethics certifications.

**Required Job Competencies**
- Deliver Results for Clients - Anticipates and addresses client needs, drives solutions with measurable impact.
- Collaborate Within Teams and Across Boundaries - Actively engages across teams, navigates diverse perspectives, resolves conflicts constructively.
- Lead and Innovate - Introd