We're working with a globally recognised financial services business looking to build on their AI function. They're well past the experiment stage, with executive backing, a growing engineering team and real budget behind the roadmap. The systems this team builds go into production and get used at serious scale, not parked in a demo workplace.

This is a newly created senior role, so you'll have a real say in how things get built rather than inheriting someone else's decisions.

You'll be the senior hands-on engineer for their LLM and GenAI work. That means owning solutions end to end, from working out whether a problem actually needs AI through to design, build, deployment and keeping it running well in production.

Day to day you'll be:
Designing and shipping LLM powered features into production, including RAG pipelines, agentic workflows and evaluation frameworks
Building and maintaining the infrastructure behind it: vector databases, embedding pipelines, model serving and monitoring
Managing cost, latency and quality trade-offs across model providers (OpenAI, Anthropic, open source)
Writing production Python and deploying on AWS or Azure with proper CI/CD




Setting engineering standards for how AI gets built across the business, including guardrails, testing and responsible use
Working closely with product managers, data engineers and stakeholders to take ideas from prototype to production
Mentoring mid-level engineers as the team grows

What you'll bring
Solid software engineering fundamentals with 5+ years experience, including recent production AI or ML work
Hands-on experience building with LLMs: RAG, prompt engineering, fine tuning, model APIs and evals
Solid Python and experience with cloud platforms (AWS or Azure)
Experience getting models into production, not just notebooks. You know what monitoring, versioning and rollback look like for AI systems
The ability to talk trade-offs with non-technical stakeholders and push back when something shouldn't be built
Full working rights in Australia

Nice to have
Experience with LangChain, LlamaIndex or similar frameworks
Classical ML background (scikit-learn, PyTorch, TensorFlow)
Exposure to MLOps tooling like MLflow, SageMaker or Azure ML
Experience in a scale-up or enterprise setting where you've built AI capability from early days

📌 Senior Ai Engineer Llm /genai Sydney
🏢 Excolo
📍 Sydney