School of Nursing Full Stack AI Engineer

The School of Nursing is seeking a Full Stack AI Engineer to design, deploy, and maintain AI applications that support nursing education and faculty research.

Responsibilities

• 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.
• Implement production large language model applications using retrieval-augmented generation (RAG), source citations, tool calling, and guardrails.
• Evaluate retrieval quality and performance, including factual grounding, citation accuracy, unsafe outputs, latency, and cost before and after release.
• Ensure factual answers are traceable to approved sources and source versions.
• Provide handling for insufficient or conflicting evidence, including declining unsupported answers and routing questions to human review.
• Develop tools for faculty authoring, content approval, and review.
• Convert educator-authored rubrics into measurable criteria, assessment logic, and evaluation cases, including faculty validation and review of AI-generated feedback.
• 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.
• 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.
• Implement automated tests, CI/CD, monitoring, backups, and recovery procedures.
• Maintain version control for code, prompts, source materials, rubrics, assessments, and AI model configurations.
• 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.
• 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.

Requirements

• Bachelor’s degree in computer science, software engineering, information systems, or a related field (or 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, including 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 the development team, with responsibility for reliability and iteration.
• 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 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.

Preferred Qualifications

• 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.

Technology Stack

• Python, TypeScript, React, Next.js
• Large language model, retrieval-augmented generation (RAG), tool calling
• Git, CI/CD, cloud deployment
• Authentication, relational databases

Working Expectations and Oversight

• 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.
• Supervisors 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.

Salary

• $70,000 annual for a 30 hour assignment

Required Application Materials

• Resume.
• Brief statement describing relevant experience.
• 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.

Application Notes (Non-UT Employees or Contingent Workers)

• Resume is prompted the first time you apply; then you can upload a new Resume for subsequent applications.
• Any additional required materials are uploaded in the Application Questions section (multi-select files).
• Before submitting, ensure all required materials are uploaded.
• After submission, you cannot make changes.

Application Notes (Current UT Employees or Contingent Workers)

• Must apply within Workday by searching for Find UT Jobs.
• If a current employee: log in to Workday, update your Worker Profile sections via the Career link before applying.
• The application is one page and prompts you to upload your resume.
• Respond to application questions to upload additional required materials noted above.

Employment Eligibility

• Regular staff employed in their current position for the last six continuous months are eligible for openings recruited through University-Wide or Open Recruiting.
• Staff eligible for promotion/transfer may apply without supervisor approval.

Retirement Plan Eligibility

• Teacher Retirement System of Texas (TRS), subject to being at least 20 hours per week and at least 135 days in length.

Background Checks

• A criminal history background check will be required for finalist(s) under consideration.

Employment Eligibility Verification (I-9)

• If hired, complete the federal Employment Eligibility Verification I-9 form.
• Present acceptable and original documents to prove identity and authorization to work in the United States.
• Documents must be presented no later than the third day of employment.
• Failure to do so will result in loss of employment at the university.

E-Verify

• The University of Texas at Austin uses E-Verify to check work authorization of all new hires effective May 2015.
• Company ID number for E-Verify: 854197.
• For more information: E-Verify Poster (English and Spanish) [PDF], Right to Work Poster (English) [PDF], Right to Work Poster (Spanish) [PDF].

Compliance (Title IX and Clery Act)

• 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 as a Campus Security Authority (Clery Act), you will be notified and provided resources for reporting.
• The Clery Act requires prospective employees be notified of the availability of the Annual Security and Fire Safety report.
• You may access the most recent report online or obtain a copy at University Compliance Services, 1616 Guadalupe Street, UTA 2.206, Austin, Texas 78701.