There's a big difference between building an AI demo and making it work reliably in production. That's where this role comes in.

You’ll join an Australian digital marketplace that’s scaled rapidly over the past few years and is now putting AI to work across its customer-facing products and internal operations. There are live agents delivering measurable results, a explicit strategy for where AI can add value, and plenty more to build following significant investment in the underlying technology platform.

The engineering team is relatively lean, which means you'll have genuine ownership of what you build and the technical decisions behind it. You'll work closely with a hands-on CTO who’s leading the AI strategy, helping shape the architecture, engineering standards and reusable frameworks that will support future development.

At its core, this is a software engineering role with a robust focus on applied AI. Building with LLMs is one thing. Making those systems reliable, scalable and maintainable in production is where the real engineering challenge lies.

You'll be responsible for:
Designing, building and deploying production AI agents across customer interactions, automation and internal workflows
Building scalable full‑stack applications in TypeScript, Node.js, React and AWS, integrating LLMs,



external APIs and agentic frameworks
Creating reusable components, orchestration patterns and guardrails that speed up AI delivery across the business
Owning technical design across architecture, integrations, reliability, security and performance
Working with product, engineering and business teams to find where AI pays off commercially
Setting the standard for testing, evaluating, monitoring and maintaining AI in production

What you bring:
Deep commercial experience building production software in TypeScript, Node.js, React and AWS
LLM-powered or agentic applications shipped to production, not left at proof of concept
Solid system design: APIs, integrations, scalability and the trade-offs that come with them
Ownership from discovery and design through to production and ongoing improvement
A transparent view of how engineering choices affect customers, operations and the bottom line
Confidence to challenge assumptions, work through ambiguity and talk to technical and non-technical people alike
LLM orchestration, tool calling and multi-agent systems
RAG and evaluation frameworks
Observability for AI applications in production
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📌 Full Stack Ai Engineer Sydney
🏢 Latitude IT
📍 Sydney