AI Application Architect

As part of the Application & Infrastructure SME team within the ICOE, you will focus on modern application architecture while pioneering the use of agentic AI in real delivery scenarios. You will collaborate closely with Avanade Regions on both direct and indirect deals, supporting them during solutioning phases as well as during critical delivery phases. Whether modernizing legacy systems or building solutions from scratch, you will apply agentic AI to transform how projects are executed end-to-end.

This is a unique opportunity to influence Avanade’s architecture direction, elevate engineering productivity, and lead high-impact initiatives across Azure, AWS, and GCP .

What you’ll 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.

• Define end-to-end architectures integrating traditional software, LLMs, vector stores, and orchestration.

• Drive AI adoption within Avanade Regions, enabling AI-driven solution roadmaps.

• Contribute to solution planning and design across multi-disciplinary and multi-cloud environments.

• 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.

• Cloud, AI engineering, or architecture certifications are a plus.

About You

• Passionate about AI with hands-on experience applying agentic patterns in real delivery work.

• Comfortable working at the intersection of software engineering, AI, cloud, and automation.

• Clear communicator across technical and non-technical stakeholders.

• Enjoy mentoring teams and raising overall AI engineering maturity.

• Continuously explore emerging AI frameworks, tools, and architectural approaches.