Economics Adjunct - Jabs School of Business

About the role

Reporting to the DINA Lead, the Artificial Intelligence (AI) Research Scientist On-Call position will play a key role in the development and advancement of an AI-driven Decision Support System (DSS). This position is responsible for designing, developing, and integrating advanced AI technologies, including real-time data processing, retrieval-augmented generation (RAG), Speech-to-Text (STT), and Text-to-Speech (TTS) models and APIs to enhance decision-making capabilities across diverse industries. The AI Research Scientist will collaborate with a multidisciplinary team of Ph.D.-level AI experts specializing in multi-cloud architectures (Azure, AWS, and Google Cloud Platform), natural language processing (NLP) pipelines, scalable knowledge graphs, and AI-driven agent frameworks. The role requires conducting applied and translational research, developing innovative AI solutions, publishing and disseminating findings where appropriate, and contributing to the deployment of scalable, production-ready systems. In addition to technical contributions, the AI Research Scientist will provide mentorship and guidance to student team members, supporting their professional development, research engagement, and technical skill development while fostering a collaborative learning environment.

Responsibilities

• Research, develop, validate, and deploy AI models, algorithms, and data pipelines for processing large-scale structured and unstructured datasets, leveraging natural language processing (NLP), knowledge graphs, and semantic search technologies.
• Design, implement, and optimize secure, scalable, and high-performance AI solutions across multi-cloud environments, including Microsoft Azure, Amazon Web Services (AWS), and Google Cloud Platform (GCP).
• Enhance and maintain retrieval-augmented generation (RAG) frameworks to improve knowledge retrieval, contextual understanding, and recommendation accuracy.
• Develop and optimize integrations with Neo4j, vector databases, and related technologies to support dynamic knowledge graph applications and advanced data relationships.
• Lead the research, development, fine-tuning, evaluation, and benchmarking of large language models (LLMs) to support automated decision-making and intelligent recommendations.
• Design, build, and deploy AI-powered agents capable of interpreting complex queries, executing automated workflows, and delivering context-aware insights and recommendations.
• Develop, integrate, and maintain Speech-to-