AI Application Architect

Role Overview

Join Avanade’s Global Integrated Center of Excellence (ICOE) as a hands-on AI Application Architect, helping design intelligent, agentic, cloud-native applications. You will apply advanced AI techniques to accelerate every phase of the delivery lifecycle - from analysis and design to build, test, deploy, and operate - driving transformation across complex enterprise landscapes.

What You Will Do

Architect AI-powered applications using autonomous and semi-autonomous agentic frameworks. Apply AI agents across all delivery phases: analysis, design, build, test, deploy, and operations. Modernise legacy applications using agentic AI for discovery, transformation, and refactoring.

Why It Might Be a Fit

This is a unique opportunity to influence Avanade’s architecture direction, elevate engineering productivity, and lead high-impact initiatives across Azure, AWS, and GCP. You will have the chance to work for Microsoft’s Global Alliance Partner of the Year (14 years running), with exceptional training (minimum 80 hours annually) and paid certifications.

Requirements

• 12+ years of experience designing and developing enterprise-scale applications
• Strong foundation in software engineering including frontend, backend, APIs, data, and cloud architecture
• Expertise in Java or C# as a primary language; hands-on experience with Python, Rust, and TypeScript/JavaScript
• Proven delivery experience applying agentic AI to modernize legacy systems or build new solutions
• Hands-on expertise with agentic AI frameworks such as AutoGen, Semantic Kernel, LangChain, or equivalents
• Ability to apply AI agents across all phases of delivery: requirements, architecture, coding, testing, documentation, and deployment
• Experience with LLMs, prompt engineering, RAG, vector databases, and orchestration patterns
• Strong Azure expertise preferred, with hands-on exposure to AWS and GCP
• Experience integrating AI into distributed systems, microservices, APIs, and event-driven architectures
• DevOps and MLOps experience including CI/CD, IaC, automated testing, observability, and deployment automation
• Familiarity with data engineering, ML models, Responsible AI, and enterprise governance
• Ability to communicate complex AI concepts to both technical and executive audiences

Benefits

• Exceptional training (minimum 80 hours annually)
• Paid certifications
• Global technical communities
• Dedicated career advisor
• Supportive colleagues who care about your success