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Databricks and AI Engineer

Bi & Dw Australia — Australia · Posted ~7 hours ago

Skills

Databricks Generative AI Large Language Models (LLMs) Vector databases Embeddings RAG pipelines Agent-based architectures Prompt engineering Fine-tuning LangChain LangGraph Cloud GenAI platforms React Angular Node.js Python Django Flask Cloud architecture MLOps DevOps Azure Azure AI Foundry Azure AI Search Prompt Shields LLMs RAG AWS Bedrock Azure OpenAI Google Vertex AI

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Summary ✨ AI‑Generated

Join a data and AI engineering team as a specialist in Databricks and generative AI. You will build intelligent systems using LLMs, vector search, RAG, agent architectures, prompt engineering, and modern orchestration frameworks. The role also requires strong full-stack development, cloud architecture, and MLOps/DevOps expertise, particularly across Azure-based AI environments.

Highlights

Work on advanced data, AI, and cloud engineering initiatives with strong exposure to generative AI, scalable architectures, and modern MLOps practices. The role combines hands-on engineering with opportunities to communicate complex technical concepts across diverse audiences.

Description

A leading Data & Analytics consultancy is looking for a Databricks engineer with strong AI skills Obviously you need DATABRICKS with bells on top but also: Deep expertise and proven experience in Generative AI technologies, including:Large Language Models (LLMs)Vector databases and embeddingsRAG pipelines and agent-based architecturesPrompt engineering, fine-tuning, and orchestration frameworks (Langchain & LangGraph experience is mandatory)Cloud-based GenAI platforms (e.g., AWS Bedrock, Azure OpenAI, Google Vertex AI)Strong full-stack engineering background, including modern front-end frameworks (e.g., React, Angular) and back-end technologies (e.g., Node.js, Python, Django, Flask).Proven expertise in cloud architecture and MLOps/DevOps, deploying and scaling AI systems on Azure with proven experience with Azure AI Foundry, Azure AI Search and Prompt Shields.Ability to communicate complex technical concepts clearly to both technical and non-technical audiences.Experience in consulting or professional services, including pre-sales, client advisory, and delivery leadership.Demonstrated success in technical leadership, mentoring teams, shaping delivery standards, and contributing to the growth of an AI or engineering practice.