The UP-AI Centre is the University of Puthisastra’s institutional centre for artificial intelligence, digital innovation and responsible AI-enabled transformation. It is being developed as a university-wide platform connecting AI, education, health, research, institutional data, digital transformation and public good. Its working framework, AI-HELP: AI for Health, Education, Learning & Public Good, reflects UP’s intention to use AI not simply as a technology, but as a means of strengthening learning, research, institutional decision‑making, operational effectiveness and societal impact.

The Centre has three overarching knowledge functions:

- Accumulate Knowledge: Strengthen how UP gathers, organises and uses institutional data, evidence and knowledge.
- Share Knowledge: Build AI capability among staff and students and translate technical developments into practical, responsible and accessible applications.
- Create Knowledge: Generate research, innovation, pilots, publications, partnerships and new intellectual outputs through applied AI.

II. Purpose of the Role

The AI Implementation and Innovation Fellow will translate the UP-AI Centre’s approved priorities into practical, sustainable and measurable applications. The role will identify university processes where AI, automation and digital tools can improve effectiveness, reduce repetitive work, strengthen teaching and learning, or create new opportunities for students and staff.

The Fellow will work across academic and professional service functions to understand and map existing workflows, prioritise appropriate use cases, lead or support the design and configuration of potential solutions, test these in controlled environments, and support their responsible adoption. Work will begin with practical,



lower-risk and achievable applications that can demonstrate value and build institutional confidence before progressing to more complex integrations.

The Fellow will apply a design-document-teach-transfer approach: identifying suitable opportunities; developing and testing solutions; documenting their operation, governance and maintenance; training staff and students; and transferring ongoing ownership to an appropriate UP unit. The objective is to build institutional capability rather than dependence on an individual specialist.

This is an implementation-focused position and does not carry responsibility for the strategic leadership or management of the UP-AI Centre. The Fellow will work under the direction of the Manager, UP-AI Centre, within priorities approved through UP’s AI governance structures.

III. Duties and Responsibilities:

The overall job description below outlines the main areas of responsibilities of the Employee: The precise work program will be jointly developed with the successful candidate during the first weeks of appointment. However, the role is expected to contribute to the following core outputs.

Output 1. University Workflow and AI Opportunity Mapping

Undertake structured engagement with academic and professional services units to understand and document selected end-to-end workflows. Identify repetitive,



stable or inefficient processes and prioritise opportunities for responsible AI-assisted improvement according to value, simplicity, risk, sustainability and institutional readiness.

Output 2. Applied AI and Automation Implementation

Lead or support the design, configuration, testing and implementation of practical AI-enabled workflows, agents, automation and related digital applications aligned with approved UP-AI priorities. Work with technical specialists where required and emphasise useful, maintainable deployment rather than experimentation for its own sake.

Output 3. AI-Enabled Learning and Teaching

Work with Digital Learning and academic faculties to identify, pilot and evaluate responsible applications of AI in curriculum development, learning design, assessment support, Moodle, staff capability development and student learning.

Output 4. Documentation and Sustainability

For each approved implementation, prepare appropriate process schematics, technical and user documentation, operating instructions, maintenance guidance, training resources, system ownership arrangements and change records. Store documentation in an approved UP repository so that successful applications can be maintained and developed by UP.

Output 5. AI Training and Capability Development

Contribute to UP’s AI Fluency and capability-building program. Subject to academic approval and workload allocation, contribute to or deliver an applied AI course or equivalent structured learning program each semester. Develop short practical workshops based on successful UP use cases and support staff and students to replicate selected functions in secure test environments.

Output 6. Student Engagement and App

📌 AI Development and Innovation Fellow (Cairns Regional)
🏢 Puthisastra
📍 Cairns Regional