Artificial Intelligence Analytics Architect
Our talented Data & AI Practice is made up of globally recognized experts - and there's room for more analytical and ambitious data professionals. If you're passionate about helping clients make better data-driven decisions to tackle their most complex business issues, let's talk. Take your skills to a new level and launch a career where you can truly do what matters.
Come join us
As an Artificial Intelligence Analytics Architect, you will bring expert-level knowledge in support of sales motions and project execution across Avanade's Data & AI portfolio. We are looking for SME who brings deep engineering experience and a strategic mindset to design, build, and operationalize enterprise AI and machine learning solutions-particularly those involving large language models (LLMs), agentic systems and operationalization of AI/ML systems. This role requires a deep understanding of AI/ML technologies, cloud platforms, and the ability to translate complex business requirements into scalable, production-ready solutions for our clients.
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What you'll do
Architect Scalable AI Solutions: Design and optimize end-to-end ML and LLM systems-including traditional ML, retrieval-augmented generation (RAG), and agentic AI architectures-that serve real-time and batch workloads at enterprise scale.
Build and Operationalize Production Systems: Lead implementation of production-ready AI solutions using tools such as Azure ML, Databricks, and Azure AI Foundry, ensuring performance, reliability, security, and compliance.
Define Best Practices and Frameworks: Collaborate with solution architects, engineers, and data scientists to set architecture standards, delivery frameworks, and reusable components that enable consistent, high-quality AI deployments.
Mentor and Enable Teams: Coach junior engineers and architects, lead technical reviews, and foster a culture of innovation and engineering excellence across AI teams at Avanade.
Drive Continuous Innovation: Stay current with advancements in AI/ML and integrate them into enterprise architectures to future-proof solutions.
Skills and experiences
AI & ML Architecture: Proven experience architecting end-to-end solutions across the ML and LLM lifecycle-from data ingestion and model training to inference, monitoring, and continuous improvement.
Strategic & Business Alignment: Ability to balance technical feasibility with business value, driving adoption of AI technologies that align with organizational priorities and customer needs.
Cloud & Data Ecosystems: Deep familiarity with Azure and with tools like Azure Functions, AKS, Event Hubs, Spark, for scalable, real-time architectures.
Programming & Tools Proficiency: Strong working knowledge in Programming/scripting languages, i.e., Python/Java, Scala, SQL, and experience across machine learning and deep learning frameworks (e.g., PyTorch, TensorFlow).
Deployment & MLOps: Understanding of modern MLOps practices, including containerization (Docker, Kubernetes), CI/CD pipelines, and observability tools.
LLMs and Agentic Systems: Experience building solutions using LLMs, with practical understanding of prompt engineering, semantic search, tool usage, and orchestrated multi-agent workflows.
Communication & Leadership: Ability to engage both technical and non-technical stakeholders, lead architecture reviews, and represent AI strategy in cross-functional conversations.
Continuous Learning: Strong curiosity and drive to stay current with the latest AI research, technologies, and tools-and apply that knowledge to build smarter, more effective solutions.
About you
Characteristics that can spell success for this role:
• Consultative, collaborative, curious
• Resilient, adaptable, flexible
• Humble leader, master negotiator, relationship builder
• Passionate about tech and engaging with and advising clients