Principal Data Scientist

Suncorp; Sydney; Hybrid; AUD 150,000 - 230,000; Full time

Job summary

Suncorp seeks a Principal Data Scientist to shape and build the next generation of AI solutions across GenAI, LLMs and AI Engineering in Australia. The role blends experimentation, solution architecture and production software engineering to deliver measurable business impact.

You’ll prototype rapidly, write production-grade Python, evaluate AI applications, and engineer observable, secure, scalable services. You’ll influence patterns and practices enabling enterprise-grade AI.

Qualifications

• 8+ years’ experience across Data Science, ML, AI, or related disciplines.
• Hands-on production AI/ML deployment experience.
• Strong Python and API/CI-CD capabilities.
• Practical Generative AI and LLM application development.

Responsibilities

• Lead design and delivery of complex Data Science and Generative AI solutions from concept to production.
• Remain hands-on across solution design, development, testing, deployment and monitoring.
• Build practical applications using LLMs, RAG, agents and AI-enabled automation.
• Establish observability, evaluation and continuous improvement for AI solutions.
• Partner with engineering, risk and business teams to embed AI into real processes.
• Provide leadership, code reviews and mentorship while actively building.

Skills

8+ years experience

Python

AI Engineering

Generative AI

LLMs

RAG & embeddings

LLM evaluation

Agentic systems

Job description

Principal Data Scientist | GenAI, LLMs & AI Engineering

Location Sydney, Melbourne or Brisbane

Go beyond the proof of concept. Build production AI that delivers real-world impact.

We’re looking for an exceptional Principal Data Scientist to help shape and build the next generation of AI solutions at Suncorp.

This is a deeply technical, hands‑on role at the intersection of Data Science, Generative AI and AI Engineering. You’ll move comfortably between experimentation, AI solution architecture and production software engineering, taking complex ideas from first principles through to secure, reliable and scalable production services.

This role is for a builder. You’ll prototype rapidly, write production-quality Python, evaluate and optimise AI applications, and help engineer services that are observable, testable, maintainable, secure and cost-effective. You’ll also influence the technical patterns and engineering practices that enable AI to move beyond experimentation and operate successfully in an enterprise environment.

The technical landscape

You’ll have the opportunity to work across LLMs, Retrieval-Augmented Generation (RAG), embeddings, vector and hybrid search, reranking, grounding, tool/function calling, agentic workflows, and human-in-the-loop patterns. Multi-agent architectures are also in scope where they are the right technical choice.

But we’re not interested in technology for technology’s sake. We’re looking for someone with the technical judgement to determine when AI creates genuine value, when a simpler approach is better, and how to balance capability with reliability, security, risk, latency and cost.

What you’ll do

• Lead the design and delivery of complex Data Science, AI and Generative AI solutions, from experimentation through to production.
• Remain hands‑on across solution design, Python development, evaluation, testing, deployment, monitoring and optimisation.
• Build practical applications using LLMs, RAG, agentic AI and AI-enabled automation.
• Establish rigorous approaches to AI evaluation, testing, observability and continuous improvement.
• Make pragmatic architectural decisions across deterministic workflows, single-agent and multi-agent solutions.
• Partner with engineering, technology, architecture, risk and business teams to embed AI into real business processes and customer experiences.
• Help establish reusable patterns and engineering practices that strengthen Data Science and AI capability.
• Provide technical leadership, design and code review, mentoring and thought leadership while continuing to build.

What you’ll bring

You’re an accomplished Data Scientist, ML Engineer or AI practitioner with significant technical depth and a track record of turning sophisticated ideas into working systems.

You’ll bring:

• 8+ years’ experience across Data Science, Machine Learning, AI, Software Engineering or closely related disciplines.
• Recent hands‑on experience building and deploying production AI/ML solutions.
• Strong Python and software engineering capability, including APIs/services, automated testing, CI/CD, deployment, monitoring and observability.
• Practical experience developing Generative AI and LLM applications.
• Strong knowledge of RAG, retrieval, embeddings, vector or hybrid search, reranking and grounding.
• Experience evaluating LLM applications across quality, groundedness, safety, reliability, latency and cost.
• An understanding of LLM risks including hallucination, prompt injection, data leakage and inappropriate model or tool behaviour.
• Experience with agentic systems including tool/function calling, workflow orchestration, state management and human-in-the-loop patterns.