AI Engineer - Agentic Engineering » Melbourne CBD, Melbourne - Knowledge: Strong knowledge of software engineering techniques and development processes and tools, for example, IDEs, SCCS, Algorithms and Data Structures, Automated testing and computer system and cloud operations Advanced proficiency with Python; working familiarity with ML frameworks such as TensorFlow or PyTorch Strong knowledge of current AI/ML technologies and their applications Team leadership and team dynamics Strong knowledge of agentic AI engineering - designing, building and orchestrating AI agents, including agent frameworks, tool/function calling, multi‑agent workflows, MCP (Model Context Protocol) servers and reusable agent skills Familiarity with modern AI-assisted engineering tools (e.g. Claude Code, Codex, Kiro, agent loops and automations) Understanding of designing and operating agent platforms on cloud (AWS preferrably), including containerisation (Docker/Kubernetes), MLOps/LLMOps and CI/CD Understanding of responsible AI, AI safety and governance - guardrails, security, data privacy, and evaluation/testing of LLM and agent applications (e.g. A/B and back-to-back testing, ModelOps/LLMOps) Experience: Minimum of 2 years' experience in a relevant AI,



machine learning or software engineering role covering solution development, implementation and deployment, with extensive commercial development in Python (or similar languages) Demonstrated experience with cloud technology (e.g. AWS, Azure or similar) and in analysing and organising structured and unstructured data Strong communication and stakeholder management skills Extensive experience in analysing and developing software applications to deliver business solutions Demonstrated experience building AI agents, MCP (Model Context Protocol) servers and reusable skills for specific business use cases, using up-to-date AI-assisted development tools (e.g. Claude Code, Codex, Kiro, agent loops and automations) Experience designing and building agent / AI platforms on cloud, delivering scalability, cost efficiency, safety, security and the evaluation/testing of agent and LLM applications Demonstrated experience in applied AI engineering, machine learning and data science, including working with language models, RAG, vector databases and knowledge graphs Experience working in and leading software engineering teams across a full-stack development environment Experience in the electricity industry desirable

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