Solution Architect - Industrial AI

A career in IBM Consulting is built on long-term client relationships and close collaboration worldwide. You'll work with leading companies across industries, helping them shape their hybrid cloud and AI journeys. With support from our strategic partners, robust IBM technology, and Red Hat, you'll have the tools to drive meaningful change and accelerate client impact. At IBM Consulting, curiosity fuels success. You'll be encouraged to challenge the norm, explore new ideas, and create innovative solutions that deliver real results. Our culture of growth and empathy focuses on your long-term career development while valuing your unique skills and experiences. As a Solution Architect: Cognitive Computing, you will design and implement cognitive solutions that run on multiple platforms and are composed of multiple software packages. You will create the technical solution architecture for a given business problem and lead the development, integration, and testing of the solution. Your primary responsibilities will include:

• Design Technical Solutions: Create the technical solution architecture for a given business problem, utilizing system engineering principles, cloud architectures, and probabilistic and stochastic systems.
• Lead Solution Development: Lead the development, integration, and testing of cognitive solutions, ensuring performance architecture and engineering of a fully functional cognitive system.
• Select Analytics Components: Choose complementary analytics components for developing solution blueprints, considering content formats, representations, data sources, content management systems, and interfaces.
• Develop Solution Blueprints: Create solution blueprints that account for the full information path from source to knowledge base and from input to processing the content in Cognitive Computing solutions.
• Integrate Cognitive Technology: Utilize the Watson technology suite and integrate cognitive technology to develop comprehensive solutions.
• System Engineering Principles: Experience with system engineering principles, including system decomposition techniques and the art of system synthesis using available cognitive technology.
• Cloud Architectures: Experience with cloud architectures and their application in designing and implementing cognitive solutions.
• Probabilistic and Stochastic Systems: Experience with probabilistic and stochastic systems, including their application in cognitive computing solutions.
• Cognitive Technology: Experience with the Watson technology suite and other cognitive technologies, including their integration and application in developing comprehensive solutions.
• Content Management Systems: Experience with content formats, representations, data sources, content management systems, and interfaces, including their application in cognitive computing solutions.
• Familiarity with Complementary Analytics: Experience with selecting and integrating complementary analytics components to develop comprehensive cognitive solutions, considering performance architecture and engineering requirements.