Senior IT Officer, Business Solutions I (AI Solutions Officer)

Senior IT Officer Business Solutions I (AI Solutions Officer)

Description

Do you want to build a career that is truly worthwhile Working at the World Bank Group provides a unique opportunity for you to help our clients solve their greatest development challenges. The World Bank Group is one of the largest sources of funding and knowledge for developing countries; a unique global partnership of five institutions dedicated to ending extreme poverty increasing shared prosperity and promoting sustainable development. With 189 member countries and more than 120 offices worldwide we work with public and private sector partners investing in groundbreaking projects and using data research and technology to develop solutions to the most urgent global challenges. For more information visit

Background& General Description

TheInformation and Technology Solutions (ITS) Vice Presidential Unit supports theWorld Bank Groups mission by delivering transformative digital solutions tostaff across 150 global locations. Within ITS the Operations Effectivenessunit (ITSEF) part of the Operations & Country Engagement Solutionsdepartment (ITSOE) leads efforts to enhance operational efficiency anddata-driven decision-making in the Banks Operations.

TheAI Operations Team within ITSEF focuses on integrating advanced AI/MLtechnologies into project workflows to improve project task team productivityautomate processes and strengthen risk management. Key solution areas includeGenerative AI Agents Chatbots Document Review and Insights &Classification.

Toadvance this vision ITSEF is hiring a Senior AI Solutions Engineer todesign and deploy ethical secure Agentic AI applications in collaboration withproduct teams AI Engineers data scientists and business stakeholders.

Toaccelerate impact ITSEF will complement foundation models with custom AImodelsincluding fine-tuned LLMs and Small Language Models (SLMs) tomeet business needs strict enterprise cost and latency constraints. TheSenior AI Solutions Engineer will lead the full custom model lifecycle (data curation supervised fine-tuning preference optimization safetyalignment evaluation and ongoing retraining) and will determine when SLMs (e.g. compact 113B parameter models) outperform larger models for on-premcloud or edge scenarios across Operations and Knowledge domains.

KeyResponsibilities

- Custom Model Strategy & Build: Own the strategy to select customize and train LLMs/SLMs (e.g. choose between RAG vs. fine-tuning or a hybrid) including dataset development SFT / LoRA / QLoRA/PEFT and knowledge distillation to meet cost/latency and dataresidency requirements.

- SLM First Approaches: Design SLM-centric solutions for constrained environments (limited GPU/CPU offline/airgapped) with quantization (e.g. INT8/INT4 AWQ GPTQ) and runtime optimizations (e.g. vLLM/TGI).

- Training & Alignment Pipelines: Stand up repeatable training/evaluation pipelines (e.g. MLflow/W&B Azure AI Studio/Prompt Flow LangSmith) covering data labeling SFT DPO/RLHF/Constitutional AI redteaming and automatic regression tests for model updates.

- Model Evaluation & Efficacy: Define business-grounded evals (task-specific metrics MTBench/arenastyle comparisons robustness/toxicity/hallucination rates) and A/B experiments with telemetry to drive adoption and confidence.

- Cost/Performance Governance: Monitor and optimize token spend throughput latency and GPU utilization; set SLOs and budget guardrails for production traffic. Team Leadership: Managing and mentoring a team of AI engineers and data scientists to deliver high-quality AI solutions.

- Responsible AI & Security: Implement policy privacy and safety controls (prompt injection defenses PII protection content filtering) and coordinate security/data governance for model cards datasheets and audit trails.

- Agentic AI Tools: Integrate custommodels into agentic frameworks (e.g. LangGraph / CrewAI) and enterprisesystems (Kubernetes microservices message buses) including tool usefunction calling and retrieval orchestration.

Selection Criteria

* Advanced degree (Masters) with 8 years of experience or Bachelors with 10 years in Computer Science Data Science Engineering or related field; or equivalent blend of education and experience.

* AI Agents: Build AI Agents and applications in generative AI AI Insights Document Review and chatbots. Knowledge of Agentic frameworks like LangGraph / CrewAI is a big plus.

* Expert in Generative AI NLP/LLMs and machine learning with hands-on experience in building end-to-end Agentic AI solutions using cloud platforms like Azure AWS GCP.

* Experienced in implementing retrieval-augmented generationusing Azure AI Search / AWS OpenSearch / GCP and other vector databases.

* Strong grasp of diverse database types(SQL graph unstructured) with the ability to design efficient data access patterns tailored for AI workloads.

* Data Pipelines: Hands-on experience building and managing data ingestion and transformation pipelines using Databricks Azure Data Factory or equivalent tools.

* Skilled in Python programming and MLOps including CI/CD pipelines model deployment microservices and integration with enterprise systems.

* Natural Language Processing (NLP): Proficiency in NLP techniques including sentiment analysis named entity recognition and machine translation using libraries like spaCy NLTK or Hugging Face Transformers.

* Reinforcement Learning: Experience in developing and implementing reinforcement learning algorithms for decision-making and predictive modeling.

* AI Infrastructure: Experience with AI infrastructure tools such as Kubernetes Docker and cloud platforms like AWS Azure or Google Cloud for deploying and scaling AI solutions.

* Hands-on model customization: Demonstrated experience training and fine-tuning open or proprietary LLMs/SLMs using techniques such as LoRA / QLoRA / PEFT instructiontuning and domain adaptation; experience with safety alignment (DPO/RLHF) strongly preferred.

* SLM production experience: Track record deploying SLMs (e.g. 113B class) with quantization prompt caching and distillation to meet tight cost/latency envelopes in enterprise settings.

* Evaluation & safety: Practical expertise defining automated eval suites (task success factuality robustness toxicity) and conducting redteam exercises for enterprise AI.

* Distributed & efficient training: Experience with FSDP / DeepSpeed / MegatronLM Ray or Databricks for efficient training; comfort sizing clusters storage and throughput.

* AI Ethics and Fairness: Understanding of ethical considerations in AI including bias detection fairness and transparency in AI models.

DesiredQualifications (Strong Plus)

* Advanced Machine Learning: Expertise in developing and deploying machine learning models using advanced algorithms and techniques.

* AI Model Interpretability: Skills in making AI models (LLMs & SLMs) interpretable and explainable to non-technical stakeholders.

* Edge AI: Proficiency in deploying AI models (SLMs) on edge devices for real-time processing and decision-making.

* Model hosting stacks: Experience operating vLLM/TGI Hugging Face Inference Endpoints Azure OpenAI/Azure AI Model Catalog AWS Bedrock or Vertex AI; familiarity with tokenizers KVcache behavior and batching.

* Model selection literacy: Practical comparisons across model families (e.g. Llama Mistral Gemma Phi) and criteria for choosing SLM vs. LLM based on accuracy latency privacy and TCO.

* Observability for LLMs/SLMs: Proficiency with prompt tracing hallucination detection guardrails PII filters and content moderation stacks.

* Certifications: Azure AI Engineer Associate Google ML Engineer SAFe for DevOps / Architects; AI Ethics certification.

RequiredJob Competencies

- Deliver Results for Clients:Proactively addresses clients stated and unstated needs. Adds value by constantly looking for a better way to get more impactful results; sets challenging stretch goals for oneself. Immerses oneself in client experiences and perspectives by asking probing questions to understand unmet needs.

- Collaborate Within Teams and Across Boundaries:Collaborates across boundaries gives your own perspective and willingly receives diverse perspectives. Appropriately involves others in decision-making and communicates with key stakeholders. Approaches conflicts as common problems to be solved. Actively seeks and considers diverse ideas and approaches displaying a sense of mutuality and respect.

- Model Stewardship & Governance: Establishes repeatable governance around datasets prompts and models; maintains model cards risk registers and change logs; ensures deployments comply with privacy and responsible AI requirements.

-Experimental Rigor: Designs hypothesis-driven experiments sets clear success metrics and makes data-informed trade-offs (accuracy vs. latency vs. cost) in collaboration with stakeholders.

- Lead and Innovate:Develops innovative solutions. Contributes new insights to understand situations and develops solutions to resolve complex problems. Adapts as circumstances require and manages the impact of ones own behavior on others in the context of WBGs values and mission. Identifies and pursues innovative approaches to resolve issues.

- Create Apply and Share Knowledge:Applies knowledge across WBG to strengthen solutions for internal and/or external clients. Leverages departments expertise and body of knowledge across WBG to strengthen internal and/or external client solutions. Seeks to learn from more experienced staff to deepen or strengthen their professional knowledge and helps others to learn.

- Make Smart Decisions:Interprets a wide range of information and pushes to move forward. Seeks diversity of information and inputs researches possible solutions and generates recommended options. Identifies and undertakes research and proposes recommendations. Based on risk analysis they make decisions in a timely manner within their own area of responsibility considering the interests and concerns of stakeholders.

- Client Understanding and Advising:Looks at issues from the clients perspective and advocates for clients within own area. Also urges others to focus on meeting client needs. Works with others across the VPU to define client needs and develop the best approach to meeting client needs.

Diversity& Inclusion
Weare an equal opportunity and inclusive employer with a dedicated and committedworkforce. We do not discriminate based on gender gender identity religionrace ethnicity sexual orientation or disability.

WBG Culture Attributes:

1. Sense of urgency: Anticipate and quickly respond to the needs of internal and external stakeholders.
2. Thoughtful risk-taking: Challenge the status quo and push boundaries to achieve greater impact.
3. Empowerment and accountability: Empower yourself and others to act and hold each other accountable for results.

World Bank Group Core Competencies

The World Bank Group offers comprehensive benefits including a retirement plan; medical life and disability insurance; and paid leave including parental leave as well as reasonable accommodations for individuals with disabilities.

We are proud to be an equal opportunity and inclusive employer with a dedicated and committed workforce and do not discriminate based on gender gender identity religion race ethnicity sexual orientation or disability.

Learn more about working at theWorld BankandIFC including our values and inspiring stories.

Required Experience:

Senior IC