Principal Engineer, Data & AI

Sydney/Melbourne

300k Super Bonus

Company overview A large, well-known financial services organisation, regulated and complex, with a big gap it wants to close in machine learning and decisioning. They're building out the capability to act on customer signals in real time and at scale, alongside an external technology partner and a team of in-house engineers. The structure is still taking shape, so there's room to influence how it's built.

Role and responsibilities

This is a senior, hands-on engineering role at principal level, sitting across the data and AI platform. You'll set technical direction for how data is built onto it and used from it, with ML and decisioning as the first priority.

Day to day, that means designing real-time and batch decisioning that turns customer signals into personalised action, and building the MLOps environment that supports it. You'll also help shape the self-serve side: how business teams build their own pipelines, publish data products and share data under clear contracts. A citizen ML application is part of the picture too.

You'll set the engineering standards and patterns that others build to, covering batch, real-time, graph and unstructured data. You'll build governance,



access control and regulatory requirements into the platform itself, and keep an eye on performance, cost and reliability. You'll also bring DevOps and SRE habits into the way the team ships.

There's an agentic angle as well. You'll build workflows where AI agents help create datasets, a step towards an AI-native approach to data engineering.

Much of the engineering capacity sits with a partner, so influence is a big part of the job. You'll challenge architecture and stack decisions, including with large vendors, and work with the platform engineering lead and product on the roadmap. You'll act as a technical lead on complex programs and coach engineers along the way.

Key technical skills

- Experience building MLOps environments
- Depth in ML engineering and decisioning
- Robust data engineering fundamentals and cloud data platform experience
- Proven influence with vendors and partners, including pushing back on big ones
- Regulated industry experience and the ability to navigate a large organisation
- Hands-on credibility at a genuinely senior level
- Personalisation, next best action or real-time decisioning in financial services or similar
- AI-native mindset and experience with agentic architectures

📌 Principal Engineer - Data & AI (Sydney)
🏢 Preacta
📍 Sydney