AI Engineer
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Summary
Six-month contract AI Engineer role in Melbourne (hybrid) building production-grade generative AI agents and LLM solutions: architecting autonomous agents, integrating them with enterprise systems and APIs, and setting up evaluation, monitoring, and governance frameworks. Core stack is Python with GenAI frameworks (LangChain/LlamaIndex/AutoGen) and cloud platforms (AWS/Azure/GCP).
Salary: AUD 900 - 1000 per day
AI Engineer | 6-Month Contract | Melbourne- Location: Melbourne, VIC (Hybrid)
- Work Type: Contract / Temp
- Classification: Information & Communication Technology > Developers / Programmers
- Rate: $900 – $1,000 / day
We are seeking a skilled AI Engineer for a 6-month contract based in Melbourne. You will drive the development and deployment of production-grade AI agents and Generative AI solutions that tackle practical business challenges.
In this hands-on contract role, you will bridge the gap between cutting-edge LLMs and robust enterprise architecture - building autonomous agents, orchestrating integrations, and establishing essential governance and monitoring frameworks.
Key Responsibilities
- Develop AI Agents: Architect and deploy custom AI agents that solve complex, real-world business problems.
- Enterprise Integration: Connect AI models and agent workflows with enterprise systems, APIs, and data repositories.
- Testing & Governance: Implement evaluation loops, latency/cost monitoring, guardrails, and security governance for safe deployment.
- Stakeholder Collaboration: Work closely with cross-functional teams to deliver secure, reliable, and production-ready AI products.
- Generative AI & Agent Orchestration: Hands-on experience building GenAI solutions, leveraging RAG, prompt design, and frameworks (e.g., LangChain, LlamaIndex, AutoGen).
- Core Technical Stack: Advanced Python programming along with strong API design and systems integration skills.
- Cloud & Enterprise: Experience deploying AI applications within cloud environments (AWS, Azure, or GCP).
- Communication: Outstanding problem-solving ability with clear stakeholder communication skills.
- Background working within Higher Education or large institutional settings.
- Experience with vector databases, fine-tuning, or open-source LLM deployments.
