Applied AI Engineer - GenAI / Databricks
About the role
We are looking for a hands-on AI Engineer to help build and iterate a practical enterprise Generative AI solution for a leading Australian financial services organisation. Working within a small multidisciplinary team, you will take requirements through to a working, testable solution using Python, Databricks and AWS Bedrock. This role will suit an engineer who enjoys solving real business problems, working closely with stakeholders and building pragmatic solutions without unnecessary over-engineering. This is a contract role, initially 3-6 months, with potential for extension. Rate negotiable based on experience and capability.
Key responsibilities
Build and iterate enterprise GenAI applications using Python and Databricks, including a lightweight Databricks Apps / Streamlit user interface.
Implement RAG and grounded enterprise knowledge retrieval, prompt orchestration, structured responses, citations and LLM tool / function calling.
Integrate approved foundation models through AWS Bedrock, including appropriate guardrails and human-in-the-loop controls.
Develop APIs and application components required to connect AI, retrieval, data and user-interface layers.
Establish practical tracing, evaluation, testing, logging and Git-based engineering practices.
Work closely with Data Engineering, business SMEs and consulting leads to prototype, demonstrate, test and refine the solution.
Help establish reusable engineering foundations that can support future AI use cases.
About you
You are a pragmatic engineer who can independently move from an agreed use case to a working solution and clearly demonstrate how it works.
Ideally, you will bring:
5+ years' relevant software, data, ML or AI engineering experience, with strong hands-on Python capability.
2+ years' practical GenAI / LLM application development experience, including RAG and grounded retrieval.
Strong hands-on experience with Databricks, APIs, Git and modern software engineering practices.
Experience building, troubleshooting and demonstrating end-to-end AI applications, rather than only developing individual models or components.
Strong understanding of LLM prompting, structured outputs, retrieval, evaluation and tool / function calling.
AWS Bedrock and Amazon Bedrock Guardrails.
Databricks Vector Search / AI retrieval capabilities, Unity Catalog and Delta.
MLflow tracing, evaluation and GenAI quality testing.
Databricks Apps and/or Streamlit/ or similar.
Experience working in a regulated or complex enterprise environment.
Eligibility: Applicants must be Australian citizens or permanent residents with unrestricted working rights in Australia. Visa sponsorship is not available for this role.
Applications: Direct applicants only. Please no recruitment agencies or third-party submissions.