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Lead AI Engineer (Generative AI)

Summary

Lead a team to integrate generative AI and LLMs into engineering practices, coach teams on safe AI use, and modernize SDLC with AI-first solutions.

  • Permanent Role Paying 160 – 170K + Super + Bonus
  • Accelerate the adoption of Generative AI for this company!
  • Melbourne CBD Office, Hybrid Model of Working, 2-3 days in office per week

Join a well‑known Australian company as a Lead AI Engineer (Generative AI)!

This role is for:

  • Someone with 2 - 4 years experience applying modern Generative AI in real delivery environments
  • Someone with a strong track record of providing technical leadership
  • Someone with a strong background in software engineering before stepping into a more AI‑focused role in recent times

What’s in it for you?

  • Join a well‑known ASX listed Australian company
  • Key Permanent Role Paying 160 – 170K + Super + Bonus
  • Great opportunity to help this company accelerate their adoption of Generative AI and by doing so uplift engineering standards and modernise the SDLC
  • Great opportunity to coach teams to safely and effectively use Generative AI and LLMs
  • Play a key role in influencing AI strategy, AI delivery, AI culture and responsible AI practices
  • Technical leadership opportunity where you’ll collaborate with a variety of stakeholders
  • Fantastic company culture and employee experience, work with colleagues that have excellent tenure in this organisation!
  • Hybrid working model outlined above

What you’ll bring?

  • 2 - 4 years experience applying modern Generative AI in real delivery environments
  • A strong track record of providing technical leadership
  • A 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.
  • The ability to define trustworthy AI metrics
  • A 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
  • A passion for embedding quality in delivery
  • Experience leading teams and driving end‑to‑end digital solutions
  • Excellent influencing skills and stakeholder management skills
  • A real passion for AI, its use and technology and innovation as a whole

Nice to Have’s Include:

  • A background in using Java, Kotlin
  • Experience with GraphQL
  • Experience with GitHub Actions
  • Experience with Edge AI patterns
  • Understanding of micro‑frontends

What you'll be doing:

  • 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 approaches to quality assurance and performance, working to automate testing through the use of AI practices
  • Fostering a culture of innovation and continuous improvement.

See also