Data and AI Architect

Introduction

Your Role And Responsibilities

• 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 Cognitive Solutions: Create technical solution architectures for business problems, utilizing system engineering principles, cloud architectures, and probabilistic and stochastic systems.
• Lead Solution Development: Guide 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: Account for the full information path from source to knowledge base and from input to processing the content in Cognitive Computing solutions.
• Engineer Cognitive Systems: Apply system decomposition techniques and system synthesis using available cognitive technology, including the Watson technology suite.

Required Technical And Professional Expertise

• Deep Understanding of System Engineering Principles: Experience with system engineering principles, cloud architectures, probabilistic and stochastic systems, and system decomposition techniques to design and implement cognitive solutions.
• Proficiency in Cognitive Technology: Deep expertise in cognitive technology, including the Watson technology suite, to select complementary analytics components and develop solution blueprints.
• Content Management Systems Knowledge: Experience with content formats, representations, data sources, content management systems, and interfaces to ensure seamless integration and processing of content in Cognitive Computing solutions.
• Performance Architecture Expertise: Experience in performance architecture and engineering of fully functional cognitive systems, considering scalability, reliability, and efficiency.
• Solution Development Leadership: Experience leading the development, integration, and testing of complex cognitive solutions, guiding cross-functional teams to achieve desired outcomes.

Preferred Technical And Professional Experience

• Familiarity with Cloud Platforms: Deep expertise in cloud architectures, including scalability, reliability, and efficiency considerations, to design and implement cognitive solutions.
• Knowledge of Probabilistic Systems: Experience with probabilistic and stochastic systems to develop solution blueprints and engineer cognitive systems.
• Understanding of Data Sources: Experience with various data sources, content formats, and representations to ensure seamless integration and processing of content in Cognitive Computing solutions.