AI Engineer / Permanent / Melbourne / up to $190,000 + super + bonus

About the Company

Our client is a well established, ASX listed FMCG and retail operations business with a national footprint and a multi decade track record. AI is a core part of how the business runs, and they're building a small, high impact team to lead that work.

They are looking for an AI Engineer to join their Melbourne team.

About the Role

This AI Engineer role is a hands on build and deploy role combining deep technical delivery with a growing stakeholder facing dimension. You'll design, build and deploy AI solutions that solve real operational problems, acting as the technical anchor between business problems and working systems, and growing into a role shaping AI adoption across the business.

Benefits

$170,000 to $190,000 + super + a bonus

This is a genuine build and own chance, not a maintenance role, with real scope to shape how AI is adopted across a large, established business. You'll work close to the business rather than buried in a back office function, with room to grow into a broader governance and adoption remit as the function matures.

Duties / Key Responsibilities

- Design, build and deploy AI models, LLM based tools and agentic workflows, including the evaluation and monitoring needed to trust them in production
- Build and maintain scalable AI infrastructure, data pipelines and integrations back into core business systems
- Own the full delivery cycle: solution design, build, testing,



validation, deployment and ongoing support
- Partner directly with stakeholders to translate requirements into technical deliverables, through UAT and into real adoption
- Contribute to AI governance, risk and compliance, keeping documentation and reusable components in good shape so capability scales past one person

Skills and Experience

- 5+ years across software development, data engineering or AI and automation, with real production experience shipping LLM powered applications
- Strong Python skills, including async work, API frameworks and solid testing practices
- Practical cloud experience running AI and ML workloads day to day, ideally with Azure, AWS or GCP exposure or certification
- Comfort with REST APIs, auth, event driven integration, relational databases and data pipelines
- Working knowledge of MLOps, DevOps and solid software engineering practice
- A track record of owning delivery end to end, including working directly with non technical stakeholders, ideally in cross functional or agile teams
- Clear written and verbal communication, with the ability to explain a technical tradeoff to a non technical audience
- Exposure to retail, supply chain or FMCG adjacent AI applications is a plus, as is an interest in AI governance and ethics
- Formal study in a relevant field is useful but not the bar. A strong body of shipped work counts for just as much

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