Join one of the most forward-thinking teams in Sydney, working within a business that is genuinelyAI-firstin its approach.
There is a defined strategy, real budget, and enterprise-wide commitment to embedding AI across products and operations.
We've recently partnered closely with the business to appoint theirEngineering Manager, and are now supporting the next phase of the build-out.
Off the back of that hire, we're adding multiple engineers to deliver on a pipeline ofgreenfield AI initiatives.
The focus is clear:strong software engineering foundations, with exposure to AI-native environments.
This is not a data science role, it's about engineers who can build thesystems and platforms that enable agentic AI at scale.
You'll be working on production-grade systems across multiple use cases, fromcustomer-facing agents and chatbots to internal AI capability, partnering closely with teams responsible for fine-tuning models.
A solid understanding ofagentic ecosystems and LLMOpswill go a long way in helping you succeed.
Overview of the Role
You'll be responsible for building and owningscalable backend systemsthat power enterprise AI solutions.
This is a hands-on engineering role, focused on writing high-quality code, automating workflows,



and creating the foundations required for AI to operate reliably in production.
Operating in a modern DevOps environment, you'll takeend-to-end ownershipacross design, build, deployment, and ongoing optimisation.
You'll work closely with data and AI teams to integrate models into real-world applications, ensuring they are performant, scalable, and maintainable.
Key Skills
5+ years software engineering experience inAgile/DevOps environments, ideally withPython (OOP)
Strongend-to-end SDLCexperience across design, build, test, and production support
Proven ability to buildscalable backend systemsand writeproduction-grade code
Experience withCI/CD pipelinesand deployments incontainerised environments (Docker/Kubernetes)
Exposure toagentic AI / LLM frameworks(e.g. RAG, MCP, Vertex AI, LangChain, LlamaIndex)
Understanding ofLLMOps practicesfor deploying, monitoring, and scaling AI models
This is a strong prospect for engineers who want to stay close to the tech, build meaningful systems, and play a key role inhow AI is actually delivered across a large enterprise.
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📌 Ai Engineer (New South Wales)
🏢 Preacta
📍 New South Wales