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AI/LLM Developer/Engineer

University of North Carolina at Chapel Hill

University of North Carolina at Chapel Hill

Software Engineering, Data Science
USD 26.04-33.85 / hour
Posted on Nov 22, 2025
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AI/LLM Developer/Engineer

Posting Information

Posting Information
Department Sch of Nursing - 440100
Career Area Information Technology
Posting Open Date 10/23/2025
Application Deadline 12/01/2025
Position Type Temporary Staff (SHRA)
Position Title AI/LLM Developer/Engineer
Position Number 20071830
Vacancy ID S026301
Full-time/Part-time Full-Time Temporary
Hours per week 40
Work Schedule
Position Location North Carolina, US
Hiring Range $26.04 - $33.85 per hour
Proposed Start Date
Estimated Duration of Appointment 6 months not to exceed 11 months
Position Information
Be a Tar Heel!
A global higher education leader in innovative teaching, research and public service, the University of North Carolina at Chapel Hill consistently ranks as one of the nation’s top public universities. Known for its beautiful campus, world-class medical care, commitment to the arts and top athletic programs, Carolina is an ideal place to teach, work and learn.
One of the best college towns and best places to live in the United States, Chapel Hill has diverse social, cultural, recreation and professional opportunities that span the campus and community.
University employees can choose from a wide range of professional training opportunities for career growth, skill development and lifelong learning and enjoy exclusive perks that include numerous retail and restaurant discounts, savings on local child care centers and special rates for performing arts events.
Primary Purpose of Organizational Unit
The mission of the School of Nursing is to enhance and improve the health and well-being of the people of North Carolina and the nation, and, as relevant and appropriate, the people of other nations, through its programs of education, research, and scholarship, and through clinical practice and community service. The University of North Carolina at Chapel Hill School of Nursing has been the leader in nursing education in North Carolina throughout its history. Established in 1950, it was the first school of nursing in North Carolina to offer a four-year baccalaureate nursing degree program followed by the first master’s degree program, the first continuing education program for nurses, first doctoral program, and first accelerated BSN option to students with college degrees. Today, the School is renowned for its academic programs, its research and its commitment to clinical and community service within state, national and global communities.
Position Summary
The Center for Virtual Care Value and Excellence (ViVE), led by Dr. Saif Khairat, is seeking an AI/LLM Developer/Engineer to join our AI research team. This is an exciting opportunity to contribute to innovative projects at the forefront of healthcare delivery improvement, leveraging Large Language Models (LLMs) and clinical data analysis.

About the Position
We are looking for individuals with a strong theoretical and practical background in large language models, machine learning, and natural language processing, combined with a collaborative spirit and a drive for problem-solving. You’ll join a multidisciplinary team that values diversity and brings together expertise in software engineering, big data, clinical informatics, and medicine.

Key Responsibilities
  • Design, fine-tune, and evaluate large language models (LLMs) tailored to domain-specific applications using techniques such as transfer learning, LoRA, and reinforcement learning with human feedback (RLHF).
  • Build intelligent applications powered by LLMs, including chatbots, virtual agents, clinical decision tools, or document analyzers, using frameworks like LangChain, LlamaIndex, or semantic search pipelines.
  • Develop scalable LLM pipelines and infrastructure, including data ingestion, preprocessing, model serving (via GPU/TPU), and continuous performance monitoring.
  • Integrate commercial and open-source LLMs (e.g., OpenAI GPT, Claude, Mistral, LLaMA) via APIs or local deployment into digital health or enterprise systems.
  • Craft and iterate prompts using advanced prompt engineering and chain-of-thought strategies to improve output relevance, tone, factuality, and task completion.
  • Implement retrieval-augmented generation (RAG) architectures to enhance context awareness using vector databases (e.g., Pinecone, FAISS, Weaviate).
  • Evaluate LLM performance using automated and human-in-the-loop methods to assess accuracy, hallucination, safety, and user satisfaction.
  • Collaborate across disciplines with data scientists, UX designers, domain experts, and MLOps to ensure usability, performance, and alignment with real-world needs.
  • Monitor and optimize system performance, including latency, throughput, token usage, and model cost-effectiveness across deployment environments.
  • Stay current with advancements in generative AI, contributing to the internal knowledge base and driving adoption of best practices for ethical and responsible LLM use.
Minimum Education and Experience Requirements
Bachelor’s degree in Computer Science, Computer Information Systems, Computer Engineering, or closely related degree from an appropriately accredited institution and three years of experience in operations analysis and design, systems programming, or closely related area; or a
- Bachelor’s degree from an appropriately accredited institution and four years of experience in operations analysis and design, systems programming or closely related area; or an Associate’s degree in Computer Information Technology, Computer Engineering Technology, or Networking Technology from an appropriately accredited institution and five years of experience in operations analysis and design, systems programming, or closely related area; or an equivalent combination of education and experience.
- Journey level requires an additional one year of education or experience.
- Advanced level requires an additional two years of education or experience.
Required Qualifications, Competencies, and Experience
  • Bachelor’s degree in Computer Science, Electrical Engineering, or related fields.
  • Expertise in Retrieval-Augmented Generation (RAG), Natural Language Processing (NLP), deep learning frameworks.
  • Proficiency in Python and frameworks such as PyTorch, TensorFlow, Hugging Face Transformers, or LangChain
  • Familiarity with clinical or healthcare data (e.g., EHRs, clinical notes, structured claims data)
  • Proven research record with peer-reviewed publications in relevant fields
  • Strong problem-solving skills and the ability to work in a collaborative environment.
Preferred Qualifications, Competencies, and Experience
  • Distributed parallel training and parameter-efficient tuning.
  • Familiarity with multi-modal foundation models, HITL techniques, and prompt engineering.
  • Experience with LLM fine-tuning, prompt engineering, or retrieval-augmented generation (RAG)
  • Experience deploying large-scale machine learning models in cloud environments.
Special Physical/Mental Requirements
Campus Security Authority Responsibilities

Not Applicable.
Special Instructions
Quick Link https://unc.peopleadmin.com/postings/308477
Temporary Employment Policies
Posting Contact Information
Office of Human Resources Contact Information
If you experience any problems accessing the system or have questions about the application process, please contact the Office of Human Resources at (919) 843-2300 or send an email to employment@unc.edu

Please note: The Office of Human Resources will not be able to provide specific updates regarding position or application status.
Equal Opportunity Employer Statement
The University is an equal opportunity employer and welcomes all to apply without regard to age, color, gender, gender expression, gender identity, genetic information, national origin, race, religion, sex, or sexual orientation. We encourage all qualified applicants to apply, including protected veterans and individuals with disabilities.

Optional and Required Documents

Required Documents
  1. Curriculum Vitae / Resume
  2. List of References
Optional Documents
  1. Cover Letter

Supplemental Questions

Required fields are indicated with an asterisk (*).

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