Graduate AI Developer
Part-time, remote research-led engineering for the university: exploring new LLM architectures, designing agentic solutions, and automating internal team workflows.
- Research emerging LLM architectures, evaluation methods and prompting strategies, then turn viable ideas into working prototypes.
- Act as solution architect for internal AI initiatives — scoping requirements, choosing models and data flow, and defining how success is measured.
- Build applied agentic LLM systems using tool calling, retrieval and multi-step orchestration to automate real internal workflows.
- Automate repetitive team processes end to end, replacing manual handoffs with auditable, reproducible pipelines.
- Work across research and delivery: communicate findings to non-specialists and ship what survives contact with real users.
- Collaborate with academics, professional services staff and other engineers on shared platform and data-governance decisions.