Job Description

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 environment.

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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.

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Sydney CBD, hybrid (3 days in office)

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$160,000 to $200,000 + super

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Permanent, full time

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Day to day you'll be:

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- Designing and shipping LLM powered features into production, including RAG pipelines, agentic workflows and evaluation frameworks
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- Building and maintaining the infrastructure behind it: vector databases, embedding pipelines, model serving and monitoring
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- Managing cost, latency and quality trade-offs across model providers (OpenAI, Anthropic, open source)
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- Writing production Python and deploying on AWS or Azure with proper CI/CD
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- Setting engineering standards for how AI gets built across the business, including guardrails, testing and responsible use
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- Working closely with product managers, data engineers and stakeholders to take ideas from prototype to production
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- Mentoring mid-level engineers as the team grows
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What you'll bring

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

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- Experience with LangChain, LlamaIndex or similar frameworks
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- Classical ML background (scikit-learn, PyTorch, TensorFlow)
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- Exposure to MLOps tooling like MLflow, SageMaker or Azure ML
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- Experience in a scale-up or enterprise environment where you've built AI capability from early days
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📌 Senior AI Engineer (LLM /GenAI) (New South Wales)
🏢 Excolo
📍 New South Wales