Our client is a large, well-established Insurance business with a long-standing presence in the Australian market. As part of a broader transformation agenda, they are investing heavily in AI capability and are building out a dedicated AI team within their Data Science & Analytics function. This is a newly created senior position within that team, created to bring deep technical leadership and strong business partnering capability to a fast-growing AI program.

About the Role

This is a hands-on senior/principal-level opportunity for an experienced AI engineer who wants more than a purely technical mandate. You'll be trusted to independently design, build and ship production-grade LLM and agentic AI systems, while also acting as the connective tissue between the AI team and the business, partnering directly with stakeholders to shape what gets built and why. You'll also be required to do deep research in order to stay ahead of the curve, with emerging AI trends. You'll operate with a high degree of autonomy, set technical direction for others, and be a visible, credible voice on AI capability, risk and chance across the organisation, equally comfortable deep in a codebase and in front of a business leader translating what's technically possible into commercial value.

Key Responsibilities

Technical delivery & leadership

- Architect, build, deploy and maintain LLM-centric and agentic AI systems, including RAG pipelines, multi-step reasoning, tool use, memory architectures and orchestration.
- Set technical direction and best practice across the team for prompt/context engineering, evaluation frameworks, and agent design patterns.
- Design and champion structured AI evaluation and testing pipelines (accuracy, hallucination, relevance, safety) and drive continuous improvement based on findings.
- Lead on AI security and responsible AI practice, identifying and mitigating threats such as prompt injection,



data leakage and model supply chain risk, and ensuring delivered solutions meet governance and compliance standards.
- Own CI/CD pipelines and containerised deployment (Docker/Kubernetes) for AI solutions, and monitor production systems for reliability and performance.

Business partnering & stakeholder engagement

- Act as a trusted advisor and primary technical point of contact for business stakeholders, translating ambiguous business problems into well-scoped, deliverable AI solutions.
- Present technical concepts, trade-offs and recommendations clearly to senior and executive audiences, influencing roadmap and investment decisions
- Collaborate cross-functionally with data scientists, ML specialists, DevOps, cybersecurity and digital product teams to ensure AI initiatives are integrated, secure and scalable
- Mentor and informally lead junior and mid-level engineers, elevating technical capability and delivery standards across the wider team

About You

- 8+ years' software engineering experience, with substantial recent focus on AI and LLM technologies at a senior or lead level
- Demonstrated, hands-on production experience with RAG pipelines, agentic patterns, and orchestration frameworks such as LangGraph, LlamaIndex or PydanticAI.
- Working knowledge of AI protocols including Model Context Protocol (MCP) and Agent-to-Agent (A2A).
- Strong track record designing and running structured AI evaluation pipelines (e.g. RAGAS, promptfoo or custom harnesses).
- Advanced context and prompt engineering skills,



including context window optimisation for production workloads at scale.
- Production-level Python and TypeScript/JavaScript, with experience building and deploying frontend, RESTful APIs and microservices.
- Fluency with AI-assisted development tooling (e.g. Cursor, Claude Code, GitHub Copilot) as a core part of daily workflow.
- Experience with CI/CD and containerised deployments (Docker, Kubernetes or equivalent).
- Applied understanding of AI ethics, responsible AI and emerging governance frameworks, and AI-specific security risks (prompt injection, PII handling, supply chain risk).
- Proven ability to engage confidently with non-technical stakeholders and business leaders, this role carries genuine business partnering scope, not just technical delivery.
- Cloud experience, Azure preferred
- Prior experience mentoring or providing technical leadership to other engineers.

Highly regarded

- Azure or AWS certifications
- Experience with LLM observability/monitoring platforms (e.g. LangSmith, Langfuse)
- Contributions to open-source AI tooling or published technical writing
- Exposure to ML model training, fine-tuning or deployment pipelines

Why Apply

This is a rare opportunity to join an established, well-resourced organisation at the ground floor of a genuine AI transformation program, with real budget, executive sponsorship, and the mandate to shape how AI is built and adopted across the business, not just bolted on. You'll have the autonomy of a principal-level technical role combined with real influence over commercial outcomes, in a collaborative team that values innovation, accountability, care and teamwork.

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📌 Principal Engineer (AI) (Melbourne)
🏢 FourQuarters Recruitment
📍 Melbourne