Generative AI Engineer

Sirius.; Sydney; On-site; AUD 150,000 - 190,000; Full time

Job summary

Sirius is partnering with a leading financial services organisation to hire a Senior AI Engineer for the AI Enablement team in Sydney. The role focuses on building enterprise-grade backend systems that enable enterprise-wide AI agent deployment, with emphasis on integrating AI/ML pipelines into existing software and leveraging graph technologies to optimise data relationships.

The ideal candidate comes from a traditional Software Engineering background and has transitioned into AI engineering,

Qualifications

• Foundational software engineering background with recent transition to AI engineering.
• Strong programming fundamentals in enterprise-grade software.
• Experience embedding AI/ML pipelines into software architectures.

Responsibilities

• Design and build scalable backend systems enabling enterprise AI agent deployment.
• Architect AI/ML pipelines and integrate into existing software using Python/Java.
• Leverage graph technologies to structure complex data relationships for AI apps.
• Utilise LLMs and modern AI tooling to overcome engineering bottlenecks.

Skills

Traditional Software Engineering

AI Engineering transition

Python

Java

Graph databases

Tools

Graph databases

Job description

I am partnering with a leading financial services organisation to find a highly skilled Senior AI Engineer to join a high-impact AI Enablement team.

This team builds the foundational platforms that empower other business areas to deploy advanced AI agents. They are specifically looking for a candidate who comes from a traditional Software Engineering background rather than a pure Data Science or Machine Learning profile who has successfully transitioned into an AI-focused engineering role. I am looking for someone with exceptionally strong core programming fundamentals who understands how to build the enterprise-grade infrastructure that makes AI integration possible.

Key Responsibilities

• Platform Engineering: Design and build scalable backend systems that enable the enterprise-wide deployment of AI agents.
• Integration & Optimisation: Architect AI/ML pipelines to integrate seamlessly into existing enterprise software, writing robust code in Python and Java.
• Data Utilisation: Leverage Graph technologies to structure and optimise complex data relationships for AI applications.
• Modern Tooling: Utilise Large Language Models (LLMs) and state-of-the‑art AI coding tools to solve complex engineering bottlenecks.

Required Skills & Experience

• Career Pathway: A strong foundational background in traditional Software Engineering, followed by a recent transition into an AI Engineering role.
• Technical Stack: Extensive commercial development experience in Python and Java, alongside proven hands‑on work with Graph databases.
• AI Integration: Practical knowledge of embedding AI/ML pipelines into software architectures, rather than building or training models from scratch.
• Problem Solving: Exceptional analytical capability to troubleshoot and scale infrastructure in a complex, high‑availability environment.