School of Nursing Full Stack AI Engineer

The School of Nursing seeks a Full Stack AI Engineer to design, deploy, and maintain reliable AI applications supporting nursing education and faculty research. Working with educators, investigators, and university technology teams, the engineer will translate teaching goals and research protocols into secure, accessible applications that can be evaluated, maintained, and used beyond an initial prototype.

Projects may include virtual patient simulations, educational assistants, research chatbots, digital self-management interventions, and tools for content review, assessment, and analytics. This is a staff position; enrollment in a degree program is not required., * Application development: Build and maintain applications using Python, TypeScript, and React or Next.js, including backend APIs, databases, authentication, role-based access, and deployment in university-approved cloud environments.

• AI engineering: Implement production large language model applications using retrieval-augmented generation (RAG), source citations, tool calling, and guardrails. Evaluate retrieval quality, factual grounding, citation accuracy, unsafe outputs, latency, and cost before and after release.
• Source traceability: Make substantive factual answers traceable to approved sources and source versions. Build clear handling for insufficient or conflicting evidence, including declining unsupported answers and directing questions to human review.
• Education workflows: Develop faculty authoring, content approval, and review tools. Translate educator-authored rubrics into measurable criteria, assessment logic, and evaluation cases, with faculty validation and review of AI-generated feedback.
• Research support: Translate investigator-approved protocols into application features, including study-specific workflows, approved intervention content, participant interactions, and reproducible data collection and exports. Implement protocol amendments in coordination with the research team.
• Assessment and analytics: Build learning assessments, learner progress tracking, and dashboards for educational outcomes, engagement, intervention delivery, and study measures. Separate educational records from research datasets and permissions as required by each project.
• Reliability and maintenance: Implement automated tests, continuous integration and deployment (CI/CD), monitoring, backups, and recovery procedures. Maintain version control for code, prompts, source materials, rubrics, assessments, and AI model configurations.
• Security and responsible use: Apply access controls, secure secret management, data minimization, and safe logging. Protect student records, research data, and inadvertently entered patient information through university-approved procedures and services.
• Collaboration and documentation: Scope projects with faculty, document architecture and operating procedures, train users, resolve technical issues, and coordinate with university IT, security, accessibility, and research support teams., Faculty retain responsibility for educational content, clinical accuracy, rubrics, assessment interpretation, and approval of source materials. Investigators retain responsibility for research protocols, consent language, and required research approvals. The engineer implements approved requirements and flags technical risks, gaps, and limitations.

Applications must clearly distinguish educational simulation and research activities from real-patient diagnosis or treatment. Any research intervention that includes health guidance must remain within its approved protocol, with defined human oversight and escalation pathways.

The supervisor and faculty partners will prioritize a manageable project portfolio within the 30-hour workweek, including maintenance and support. Work schedule, reporting relationship, formal job classification, benefits, and exemption status will be finalized through university HR., Submit a resume, a brief statement describing relevant experience, and examples of deployed applications or a portfolio. Describe your individual contribution, deployment approach, evaluation methods, and maintenance responsibilities. Confidential or proprietary materials are not required., The retirement plan for this position is Teacher Retirement System of Texas (TRS), subject to the position being at least 20 hours per week and at least 135 days in length., Employees may be required to report violations of law under Title IX and the Jeanne Clery Disclosure of Campus Security Policy and Crime Statistics Act (Clery Act). If this position is identified a Campus Security Authority (Clery Act), you will be notified and provided resources for reporting. Responsible employees under Title IX are defined and outlined in HOP-3031.

• Bachelor’s degree in computer science, software engineering, information systems, or a related field, or an equivalent combination of relevant education and experience, subject to the approved university job classification.
• Demonstrated proficiency in Python and TypeScript and experience developing applications with React or Next.js, backend APIs, relational or other appropriate databases, authentication, Git, and cloud deployment.
• Demonstrated experience deploying and maintaining at least one LLM-enabled application used by people beyond its development team, with responsibility for reliability and iteration. Relevant paid, research, or independently developed work may qualify.
• Practical experience with RAG, citations, tool calling, guardrails, and repeatable LLM evaluations, including recognition of hallucinations, prompt injection, and limitations of AI-generated assessments.
• Experience with automated testing, monitoring, and CI/CD, and working knowledge of application security, privacy, and accessibility fundamentals.
• Ability to translate faculty-defined learning objectives, rubrics, and research requirements into testable software behavior and to communicate technical choices clearly to nontechnical collaborators.
• Ability to manage competing priorities, estimate effort, document decisions, and maintain software through deployment and ongoing support., * Current enrollment in, or completion of, a master’s program in artificial intelligence, computer science, data science, or a related field.
• Experience with nursing or health professions education, virtual patient simulation, digital health interventions, or human participant research.
• Experience building content-management, educator-review, content-approval, learning assessment, and analytics workflows.
• Experience with Canvas or Moodle integration, LTI, xAPI, or SCORM, and with university identity and access systems.
• Experience implementing accessible interfaces, including keyboard and screen-reader access, and age-appropriate, user-centered user experiences.

Working expectations and oversight, A criminal history background check will be required for finalist(s) under consideration for this position., * E-Verify Poster (English and Spanish) [PDF]

• Right to Work Poster (English) [PDF]
• Right to Work Poster (Spanish) [PDF]

$70,000 annual for 30 hour assignment

The Clery Act requires all prospective employees be notified of the availability of the Annual Security and Fire Safety report. You may access the most recent report here or obtain a copy at University Compliance Services, 1616 Guadalupe Street, UTA 2.206, Austin, Texas 78701.