AI Strategy & Solution Architect

AI Architect

Role Summary

As an AI Architect at Avanade, you will lead the design and delivery of enterprise-scale AI, Generative AI, and Agentic AI solutions that help clients reinvent business processes and create measurable business value. You will work at the intersection of business strategy, solution architecture, data platforms, and AI engineering to define AI roadmaps, architect intelligent systems, and guide multidisciplinary teams from concept through production.

The ideal candidate combines deep expertise in Azure AI technologies, AI Agents, Agentic frameworks, enterprise architecture, and modern data platforms with strong consulting, stakeholder engagement, and solution leadership capabilities.

Key Responsibilities

AI Strategy & Solution Architecture

Lead AI discovery workshops and help clients identify high-value AI and Agentic AI opportunities.

Define AI transformation roadmaps aligned to business goals, operating models, and technology strategy.

Architect enterprise AI platforms and solutions leveraging Azure AI Foundry, Azure OpenAI, Microsoft Fabric, Databricks, and Azure services.

Provide executive-level guidance on AI adoption, governance, risk, and business value realization.

Agentic AI & Intelligent Systems Design

Design AI Agent ecosystems that support planning, reasoning, tool usage, workflow orchestration, and autonomous execution.

Define architectures for multi-agent systems, enterprise copilots, digital assistants, and intelligent automation solutions.

Architect Retrieval-Augmented Generation (RAG), enterprise knowledge systems, semantic search, memory patterns, and contextual grounding strategies.

Establish scalable approaches for integrating AI Agents with enterprise applications, data sources, and business processes.

Technical Leadership

Lead solution design activities across AI Engineers, Data Engineers, Software Engineers, and Architects.

Define reference architectures, reusable accelerators, development standards, and engineering best practices.

Guide teams on architecture decisions, scalability, security, performance, observability, and operational readiness.

Support major pursuits, proposals, solution estimates, and architecture reviews.

Responsible AI & Governance

Define Responsible AI, security, privacy, and governance controls for enterprise AI solutions.

Ensure AI solutions align with regulatory, compliance, and organizational risk requirements.

Establish evaluation, monitoring, and AI quality assurance frameworks.

Drive adoption of MLOps, LLMOps, and AI operational excellence practices.

Client Leadership

Act as trusted advisor to C-level executives, technology leaders, and business stakeholders.

Communicate complex technical concepts clearly to both technical and non-technical audiences.

Lead architecture discussions, executive presentations, and steering committee engagements.

Mentor architects and engineers while contributing to Avanade's AI thought leadership.

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Required Skills & Experience

AI & Agentic AI

Extensive experience designing and delivering AI and Generative AI solutions in enterprise environments.

Deep understanding of LLMs, prompt engineering, AI evaluation, agent architectures, and reasoning frameworks.

Hands-on experience with AI Agents, Agentic workflows, and autonomous systems.

Experience with RAG architectures, embeddings, vector databases, semantic search, and enterprise knowledge platforms.

Microsoft AI & Cloud Technologies

Strong experience with:

Azure AI Foundry

Azure OpenAI Service

Azure AI Search

Azure Machine Learning

Azure Data Services

Microsoft Fabric

Copilot technologies

Experience architecting cloud-native solutions on Microsoft Azure.

Agentic & AI Engineering Frameworks

Experience with one or more of:

Semantic Kernel

AutoGen

LangGraph

LangChain

CrewAI

Microsoft Agent frameworks

Understanding of orchestration, memory management, tool integration, and multi-agent collaboration patterns.

Data & Analytics

Strong understanding of modern data architectures and data engineering practices.

Experience with data governance, metadata, knowledge management, and enterprise data platforms.

Knowledge of Databricks, Fabric Lakehouse, Azure Data Platform, and enterprise information management patterns.

Consulting & Leadership

Proven experience leading architecture and solution design engagements.

Experience engaging senior business and technology stakeholders.

Strong commercial awareness, estimation, and proposal development capabilities.

Ability to lead distributed, multidisciplinary delivery teams.

Preferred Qualifications

Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, Engineering, or related discipline.

Microsoft AI and Azure certifications.

Experience delivering AI solutions in regulated industries such as Financial Services, Government, Utilities, Telecommunications, or Healthcare.

Experience with enterprise transformation and operating model change initiatives.

Work Rights: Australian Citizens preferred; Permanent Residents also welcome to apply.

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