The roleYou'll build and deploy LLM-powered applications and agentic workflows that solve real problems for teams across the organisation. The work spans agent design, tool integration, retrieval, evaluation and guardrails, through to secure production deployment. You'll work with architects, data engineers and business stakeholders, and have a real say in how solutions are designed, not just implemented.

• What you'll bringProduction experience building with LLM APIs (any major provider), beyond prototypes or internal demos
• Agentic patterns: tool use, multi-step orchestration, function calling, MCP or similar
• RAG pipelines: chunking, embeddings, vector databases, retrieval tuning
• Strong Python and API development
• Cloud deployment on AWS, Azure or GCP, including managed AI services (Bedrock, Azure OpenAI or Vertex AI)
• Evaluation, testing and guardrails for LLM outputs
• Comfortable working with business stakeholders to shape requirements
• Australian citizenship or PR

• Good to haveFrameworks such as LangGraph, LlamaIndex or similar
• Observability and LLMOps tooling
• Security and responsible AI considerations in a regulated environment
• Data engineering fundamentals

• What's on offerCompetitive salary matched to level, mid to senior
• Hybrid, Sydney or Melbourne
• Permanent
• Work across multiple models and platforms on large-scale, real-world problems
• 
  

The roleYou'll build and deploy LLM-powered applications and agentic workflows that solve real problems for teams across the organisation. The work spans agent design, tool integration, retrieval, evaluation and guardrails, through to secure production deployment. You'll work with architects, data engineers and business stakeholders, and have a real say in how solutions are designed, not just implemented.

• What you'll bringProduction experience building with LLM APIs (any major provider), beyond prototypes or internal demos
• Agentic patterns: tool use, multi-step orchestration, function calling, MCP or similar
• RAG pipelines: chunking, embeddings, vector databases, retrieval tuning
• Strong Python and API development
• Cloud deployment on AWS, Azure or GCP, including managed AI services (Bedrock, Azure OpenAI or Vertex AI)
• Evaluation, testing and guardrails for LLM outputs
• Comfortable working with business stakeholders to shape requirements
• Australian citizenship or PR

• Good to haveFrameworks such as LangGraph, LlamaIndex or similar
• Observability and LLMOps tooling
• Security and responsible AI considerations in a regulated environment
• Data engineering fundamentals

• What's on offerCompetitive salary matched to level, mid to senior
• Hybrid, Sydney or Melbourne
• Permanent
• Work across multiple models and platforms on large-scale, real-world problems
•