Design, develop, and test AI agents and LLM-based pipelines that automate multi-step research and clinical-support tasks. Implement retrieval-augmented generation (RAG) and tool-use workflows to ground AI systems in institutional data and literature. Integrate AI components with internal data sources, APIs, and research applications under appropriate data-governance controls. Evaluate model and agent performance for accuracy, reliability, safety, and bias; document results and iterate based on findings. Collaborate with investigators to translate research questions into technical requirements and prototypes. Write clean, well-documented, reproducible code and maintain version-controlled repositories. Contribute to technical documentation, internal demos, and occasional grant or publication deliverables. Stay current with developments in agentic AI frameworks and apply relevant advances responsibly. Conducts activities in a professional and ethical manner, and in accordance with KUMC Policies and applicable local, state and federal laws and regulations. Performs job responsibilities in a safe and secure manner. Coordinate work with other University areas ensure integration and support of the University mission. Develops, maintains and expands job-specific knowledge and skills to keep pace with industry changes and supports the university's commitment to excellence and innovation. Participates in relevant committees, task force, or other similar activities. Maintain confidentiality of medical center, employee, and patient information. Manages sensitive data with discretion and in accordance with KUMC policies and legal requirements. Maintains the highest standards of integrity, respect, professional conduct, and ethical standards. Bachelor's degree in computer science, data science, engineering, or a related field. 8 years of experience that requires proficiency in Python and familiarity with modern software-development practices (Git, testing, code review). Education may be substituted for experience on a year for year basis. Experience in a position that requires an understanding of machine learning and large language models, including prompting and basic evaluation. Exposure to at least one agentic or LLM framework (e.g., LangChain, LlamaIndex, the OpenAI or Anthropic SDKs, or similar) through coursework, internships, or personal projects. Graduate Certificate in Artificial Intelligence (AI) Experience building RAG systems, tool-using agents, or workflow automation with LLMs. Familiarity with cloud platforms (AWS, Azure, or GCP) and containerization (Docker). Interest in or exposure to healthcare, biomedical, or clinical-research data. Awareness of data privacy and security considerations, including HIPAA, in research or healthcare contexts. Contributions to open-source projects, research, or a portfolio demonstrating applied AI work.

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