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

• Strong 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

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

• Strong 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