AI Engineer

Contract Type

Contract/temporary

Location

VIC

Industry

Technology

Contact Name

Ty Erasmus

Contact Email

Contact Phone

Date Published

03-Jun-2026

Contract Length: 6 Months
Working Model: Hybrid
Location: Melbourne CBD
Start Date: Immediate

About the Project

A large Australian Education institute is undertaking a significant transformation of its curriculum delivery model, with a defined program of work already underway. This role sits within a dedicated AI and Advanced Analytics function, embedded directly into the transformation delivery effort.

The use cases for this engagement are already defined and partially validated, spanning learning outcome analysis, assessment classification, alignment mapping, and learning progression. The constraint is engineering capacity, not concept or demand. This engagement exists to accelerate delivery beyond current timelines, translate validated concepts into working production solutions, and establish a scalable technical foundation for broader transformation.

The AI function provides technical leadership, quality control, platform governance, and a pathway to permanent conversion. Day-to-day delivery priorities are set by the program team. The successful candidate will build for production, not proof of concept.

Job Responsibilities
  • Build agent-based and workflow-driven AI solutions aligned to defined curriculum intelligence use cases
  • Implement RAG and Copilot-style solutions using reusable, scalable patterns
  • Translate requirements into production-ready AI services, not prototypes
  • Develop reusable components including prompt frameworks, retrieval patterns, and orchestration pipelines
  • Integrate solutions with the Microsoft ecosystem: Copilot, Power Platform, and M365
  • Build secure, scalable integrations using approved APIs and enterprise connector
  • Align to enterprise architecture patterns covering identity, RBAC, and data access controls
  • Implement evaluation-led delivery with defined acceptance criteria and quality thresholds
  • Establish observability across latency, cost, and output quality metrics
  • Set up safe failure and rollback mechanisms, and CI/CD pipelines for AI solutions
  • Build reusable components to enable scale beyond initial use cases
How to Apply
Click the Apply button below, for further information reach out to terasmus@quinnallan.com.au


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