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Sydney, International House, 3 Sussex St, Australia
Hybrid
AI Engineer
Role Summary
As an AI Engineer at Avanade, you will design, build, and deploy next-generation AI solutions powered by Large Language Models (LLMs), AI Agents, and Agentic AI frameworks. Working at the intersection of AI, software engineering, and cloud platforms, you will develop intelligent applications that leverage Azure AI Foundry, Azure OpenAI, autonomous agents, enterprise knowledge systems, and modern data platforms to help clients reinvent business processes and create measurable business value.
Key Responsibilities
Design and develop AI-powered applications using Azure AI Foundry, Azure OpenAI, and emerging AI technologies.
Build and orchestrate AI Agents capable of planning, reasoning, tool usage, workflow automation, and multi-agent collaboration.
Develop Agentic AI solutions using frameworks such as Semantic Kernel, AutoGen, LangChain, CrewAI, and Microsoft Agent frameworks.
Implement Retrieval-Augmented Generation (RAG), vector search, knowledge engineering, and enterprise AI patterns.
Engineer secure and scalable AI solutions integrating enterprise data, business applications, and digital platforms.
Deploy, monitor, evaluate, and optimize AI systems using MLOps, LLMOps, observability, and responsible AI practices.
Collaborate with clients, architects, and cross-functional teams to translate business challenges into AI-powered outcomes.
Contribute to innovation, reusable accelerators, and thought leadership in Generative AI and Agentic AI.
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Skills & Experience
Strong software engineering skills in Python, C#, JavaScript/TypeScript, REST APIs, and cloud-native architectures.
Hands-on experience with Azure AI Foundry, Azure OpenAI Service, Azure AI Search, Azure AI Agents, and Azure Machine Learning.
Experience building AI Agents, Copilots, and Agentic workflows leveraging tool calling, memory, orchestration, and planning capabilities.
Knowledge of Agentic frameworks such as Semantic Kernel, AutoGen, LangGraph, LangChain, CrewAI, or equivalent platforms.
Experience implementing RAG, vector databases, embeddings, prompt engineering, evaluation frameworks, and knowledge retrieval architectures.
Understanding of modern data platforms including Microsoft Fabric, Databricks, Azure Data Services, and enterprise knowledge foundations.
Familiarity with MLOps, LLMOps, Responsible AI, security, governance, and compliance practices.
Strong consulting, stakeholder engagement, and problem-solving capabilities.
What Success Looks Like
Delivering production-grade AI applications and AI Agent ecosystems that drive measurable business outcomes.
Accelerating client adoption of AI through secure, scalable, and responsible solutions.
Helping organizations evolve from AI experimentation to AI-enabled business transformation and autonomous business processes.
What You'll Bring
A passion for innovation, a growth mindset, and the ability to combine deep technical expertise with consulting skills to help clients realize measurable business value through AI.
Location: Brisbane/Sydney, or Melbourne
Work Rights: Australian Citizens preferred; Permanent Residents also welcome to apply.
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