AI Engineer - Local only

Role Overview

The AI Engineer will be a key contributor to the client’s digital transformation initiatives. This role focuses on designing, developing, and deploying scalable, ethical AI solutions to improve operational efficiency, automate decision-making, and support strategic initiatives for environmental and social programs.

Experience

• Minimum 3+ years of hands-on experience in AI/ML model development and deployment.
• Strong experience with LLMs, RAG, NLP, and Generative AI solutions.
• Experience with MLOps, Docker, and cloud platforms (AWS, Azure, or Google Cloud Platform).

Key Responsibilities

AI Solution Development

• Design, develop, train, validate, and optimize AI/ML models.
• Implement Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), NLP models, and GenAI solutions.
• Translate business requirements into technical specifications.

AI Solution Implementation & Operations

• Deploy AI models into production environments.
• Perform ongoing model training, monitoring, troubleshooting, and fine-tuning.
• Manage MLOps pipelines using tools such as MLflow and Docker.
• Ensure compliance with ethical AI standards and data governance policies.

Data Analysis & Research

• Collect, preprocess, and engineer large structured and unstructured datasets (including geospatial data).
• Recommend and implement data cleaning and preparation strategies.
• Monitor data quality, detect bias, and manage model/data drift.
• Research emerging AI technologies and recommend enhancements.

User Enablement & Documentation

• Conduct training sessions for stakeholders.
• Develop technical documentation and user guides to support adoption.

Governance, Strategy & Support

• Advise World Bank Group staff on AI strategy and policy implications.
• Contribute to AI roadmap, innovation agenda, and long-term enhancements.
• Provide continuous support and maintenance for existing AI solutions.

Required Qualifications

Education

Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field.

Technical Skills

• Proficiency in Python, TensorFlow, PyTorch, and NLP frameworks.
• Experience with Azure AI, Google Vertex AI/Search, and Vector Databases.
• Strong knowledge of deep learning, computer vision, and large language models.
• Experience with REST APIs, NoSQL, and RDBMS.
• API Management experience for integrating multiple data sources.

Preferred Certifications

• Microsoft Certified: Azure AI Engineer Associate
• Google Machine Learning Engineer
• SAFe Agile Software Engineer (ASE)
• Certification in AI Ethics

Deliverables / Milestones

• Develop Proof of Concepts (POCs) to assess feasibility of AI use cases
• Develop, train, and deploy AI models aligned to business objectives.