Staff AI Solution Architect

Job Description Summary The Staff AI Solution Architect will lead the design, development, and deployment of AI-driven enterprise applications supporting data analytics across global functions like Finance and Sourcing. This role involves full lifecycle ownership of AI components using technologies such as Databricks and AWS, ensuring scalable and standardized solutions. Key responsibilities include strategic planning, architecture design, compliance with GDPR/SOX, and integration of Responsible AI practices. The architect will collaborate across teams to shape product roadmaps, drive AI adoption, and deliver measurable outcomes aligned with business goals. Strong technical expertise, leadership, and a data-driven mindset are essential for success in this role. Job Description The Staff AI Solution Architect will be responsible for leading the design, development, and support of AI-driven enterprise applications and services that enable data analytics across global functions—including Finance, Treasury, Sourcing, and Enabling Functions. This role entails end-to-end ownership of AI components, encompassing architecture, testing, documentation, and deployment within large-scale data analytics programs. The architect will leverage technologies such as Databricks, Microsoft data fabric, Microsoft AI Foundary and AWS to build scalable, standardized AI solutions that deliver measurable value through the Safety, Quality, Delivery, and Cost (SQDC) framework, with a strong emphasis on the impact of AI initiatives on business. Key Responsibilities Strategic Collaboration: Engage in technical and business discussions to shape the future of AI solution architecture. Architecture Planning: Analyze current and future states to develop implementation roadmaps for AI solutions. Requirements Gathering: Translate business needs into architectural requirements and contribute to infrastructure governance. Solution Development: Partner with service providers to build AI solutions aligned with project goals and enterprise standards. Compliance & Standardization: Ensure AI solutions adhere to architectural frameworks and comply with GDPR, SOX, and Responsible AI guidelines. Technology Adoption: Research emerging AI technologies and trends to enhance solution design, and explore new capabilities in Databricks and Microsoft. Performance & Security Oversight: Monitor deployed solutions to ensure optimal performance and security compliance. Additional Responsibilities Solution Ownership: Collaborate with cross-functional teams, including Data Architecture and Analytics, to define and execute AI solution roadmaps aligned with business strategy. Product Roadmap Input: Work with product managers and data architects to shape analytics product roadmaps. Technical Integration: Partner with data scientists, engineers, and designers to ensure robust, scalable AI implementations.