LLMOps Engineer
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Description
Contract | Up to $1,050 per day + super | Sydney
We're partnering with a leading Sydney-based insurance organisation seeking a hands-on LLMOps / Generative AI Engineer to build enterprise AI solutions using LLMs, RAG and AI agents.
Despite the LLMOps title, this is primarily a build-focused engineering role. You'll take business use cases and turn them into secure, scalable and production-ready GenAI solutions. It is not a traditional DevOps or infrastructure position centred on deployment pipelines.
What you'll be doing
- Design and build enterprise GenAI solutions using LLMs, RAG and agentic AI
- Develop hands-on solutions in Python
- Work with business stakeholders to identify and refine valuable AI use cases
- Translate business requirements into practical, scalable technical solutions
- Build using platforms such as Azure OpenAI, Azure AI Foundry and Databricks
- Consider monitoring, performance, governance, security and cost throughout the solution lifecycle
- Integrate GenAI capabilities into existing enterprise platforms and applications
- Coordinate delivery across business, technology, onshore and offshore teams
- Develop reusable frameworks, standards and engineering patterns
- Ensure solutions align with responsible AI, risk and security requirements
What we're looking for
- Commercial experience building AI, machine learning or Generative AI solutions
- Strong hands-on Python development skills
- Practical experience working with LLMs and RAG
- Exposure to AI agents, agentic workflows or orchestration frameworks
- Experience with Azure OpenAI, Azure AI Foundry, Databricks or similar platforms
- Understanding of prompt engineering, embeddings, vector search and retrieval patterns
- Experience taking AI solutions beyond proof-of-concept stage
- Ability to work directly with stakeholders and turn loosely defined ideas into working solutions
- Understanding of production considerations including monitoring, performance, security, governance and cost
Experience in insurance, financial services or another regulated environment would be advantageous.
This role would suit a Generative AI Engineer, LLM Engineer, Applied AI Engineer or Machine Learning Engineer who enjoys building real enterprise solutions-not someone focused solely on MLOps infrastructure and deployment automation.
If you've been building LLM, RAG or agentic AI solutions and want to work on practical enterprise use cases, apply now or get in touch for a confidential discussion.