Avanade

Do you want to help shape the future of AI-powered work? At Avanade, you'll have the opportunity to design, build, and deploy cutting-edge Generative AI and Agentic AI solutions using the latest Microsoft technologies.

We are seeking an innovative and hands-on AI Engineer to join our Data & AI practice. In this role, you will work alongside clients and multidisciplinary teams to develop intelligent solutions that solve real business challenges using Large Language Models (LLMs), AI agents, automation, and Microsoft AI platforms.

The ideal candidate combines strong software engineering fundamentals with a passion for emerging AI technologies and a desire to continuously learn, experiment, and innovate.

You will join a vibrant community of AI specialists, architects, engineers, and consultants who are helping organisations transform how they work through AI.

About the Role

As an AI Engineer, you will design and develop AI-powered applications, copilots, and agentic solutions across the Microsoft ecosystem. You will work closely with clients to understand business challenges, identify opportunities for AI adoption, and translate requirements into secure, scalable, and production-ready solutions.

The role combines hands-on engineering, solution design, rapid prototyping, client-facing consulting, and continuous innovation.

You will contribute across the full solution lifecycle—from discovery and proof of concept through to deployment, evaluation, and optimisation.

Key Responsibilities:

In this role, you will:

• Design, develop, and deploy AI-powered applications and agentic solutions using Microsoft AI technologies.
• Build intelligent agents, copilots, and workflow automation solutions using Microsoft Copilot Studio, Microsoft 365 Copilot, Azure AI Foundry, and related services.
• Develop APIs, integrations, and backend services using Python and modern application frameworks.
• Create proof of concepts and prototypes to demonstrate emerging AI capabilities and business value.
• Implement prompt engineering, orchestration, grounding, and retrieval techniques to improve AI performance and reliability.
• Build and optimise Retrieval-Augmented Generation (RAG) solutions and knowledge retrieval experiences.
• Contribute to AI solution architecture, technical design, development, testing, deployment, and documentation.
• Participate in client workshops, discovery sessions, demonstrations, and technical discussions with both business and technical stakeholders.
• Apply Responsible AI principles, governance controls, and evaluation frameworks throughout the AI development lifecycle.
• Collaborate with architects, engineers, consultants, analysts, and client teams within agile delivery environments.
• Stay current with emerging AI technologies, tools, frameworks, and industry trends, sharing knowledge across the wider practice.

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