Senior Analyst IT, Research Computing - AI Engagement Specialist Research Computing at Duke University is looking for a Senior Analyst IT, Research Computing AI Engagement Specialist to help researchers effectively use artificial intelligence in their work. In this role, you will partner directly with faculty, students, and research staff to integrate AI tools-such as large language models, notebooks, and emerging AI platforms-into everyday research workflows. You will focus on adoption, usability, and real research impact, helping translate complex research problems into practical, AI-assisted solutions. If you enjoy teaching, consulting, and building bridges between advanced computing services and researcher needs, this role offers an opportunity to shape how AI accelerates discovery at Duke. Minimum Requirements: - Bachelor's degree in a quantitative, scientific, or computational discipline, or equivalent experience. - Strong proficiency in scientific programming and analysis (e.g., Python, MATLAB, R, C/C++). - Experience working in research computing or HPC environments. - Ability to translate research goals into effective computational workflows. - Strong communication and facilitation skills for working with diverse research communities. Preferred Qualifications: - Experience supporting or conducting academic research. - Familiarity with machine learning frameworks such as PyTorch, TensorFlow, or Scikit-learn. - Experience with AI tools (e.g., copilots, LLMs) in coding and data analysis workflows. - Experience designing or delivering technical training or workshops. - Advanced degree in a computational, engineering, or scientific field. Work Arrangement: This position is hybrid eligible. Work is primarily based in Durham, NC, with approximately two on-site days per month and occasional travel within North Carolina. Be Bold. - Partner with researchers to integrate AI tools into coding, data analysis, and documentation workflows. - Provide one-on-one consultations and embedded support for research groups adopting AI-enabled workflows. - Design and deliver workshops on AI-assisted coding, LLMs in research, and reproducible AI workflows. - Lead and contribute to semester-based collaborative AI research projects. - Develop documentation, tutorials, and example workflows to support scalable AI adoption.