Lead AI Engineer (Generative AI) Well‑known Australian company. Permanent role paying 160‑170K + Super + Bonus. Location: Melbourne CBD Office, hybrid model (2‑3 days in office per week). Accelerate the adoption of Generative AI for this company. Qualifications 2‑4 years experience applying modern Generative AI in real delivery environments Strong track record of providing technical leadership Strong background in software engineering before stepping into a more AI‑focused role in recent times Deep expertise in Generative AI, large language models, retrieval‑augmented generation (RAG), and modern machine learning techniques Strengths in prompt engineering, offline/online evaluation, safety guardrails, and telemetry‑driven improvement Practical experience with RAG, embeddings/vector search, and tool‑use/function‑calling orchestration Ability to define trustworthy AI metrics Software engineering background using the likes of React, Typescript, React Native AWS experience / certifications Strong knowledge of CI/CD Experience with monitoring tools Great communication skills with the ability to be a bridge between teams and bring them together Passion for embedding quality in delivery Experience leading teams and driving end‑to‑end digital solutions Design documentation skills Excellent influencing skills and stakeholder management skills Real passion for AI, its use and technology and innovation as a whole Nice to Have Background in using Java, Kotlin Experience with GraphQL Experience with GitHub Actions Kafka/Kinesis experience Experience with Edge AI patterns Understanding of micro‑frontends Responsibilities Accelerating the adoption of Generative AI for this company, leading the adoption of AI‑first engineering practices and an "AI‑first" mindset Providing technical leadership and shaping AI‑enabled solutions Reporting into the Head of Technology and working closely with the Head of Enterprise AI Collaborating with a variety of cross‑functional teams including Engineering, QA, BA, Product Management, Senior Business Stakeholders, Data Science, Cyber Security, Enterprise Architecture Coaching and training engineers and leaders in the organisation in safe, effective AI‑assisted development Encouraging teams to embed AI‑driven thinking in solution design and delivery Defining and helping to operationalise trustworthy metrics to measure the impact of AI features, and developer productivity uplifts Producing AI‑augmented solution designs when required Driving engineering excellence by uplifting standards, modernising technical practices, and championing AI‑aligned SDLC patterns Upskilling teams on AI/LLM Uplifting agentic workflows, prompt engineering, model evaluation and telemetry‑driven validation Automating guardrails Automating approaches to quality assurance and performance, working to automate testing through the use of AI practices Fostering a culture of innovation and continuous improvement Providing solution designs #J-18808-Ljbffr