Ai Domain Architect

Overview With data deeply embedded in our DNA PepsiCo Data Analytics and AI D AI transforms data into consumer delight We build and organize business-ready data and AI allowing PepsiCo s leaders to solve problems with the highest degree of confidence Our data analytics AI products and services ensure our digital transformation is delivered at scale enabling new revenue streams deeper partner relationships new consumer experiences and innovation across the enterprise As part of the Global Data AI Architecture team Architects are responsible for making PepsiCo s strategic vision real by defining the right architecture for conceiving initiating and shepherding high-priority data analytics and AI enabling capabilities The successful candidate will have a deep knowledge of AI domain know how to simplify multi-faceted concepts into succinct messaging that sets and drives strategic direction and have a proven ability to work with others on complex projects Responsibilities Defines AI north star architecture and tech strategy leads tech evaluation and selection including POCs and secures alignment across the following stakeholders AI Solutions and Platform Data Science Enterprise Solutions and Digital Products and Applications team Defines AI architecture principles and design patterns to support all types of AI ML DL Generative AI to guide and contextualize AI solution development Perform regular and thorough market research both with our existing product vendors 3rd party research agencies like Gartner and prospective vendors to stay one step ahead of the latest trends in the AI space Evolve technology strategy and north star architecture accordingly Evaluates existing AI architectures and lays out roadmap to achieve north star architecture driving rationalization of existing AI solutions across the enterprise Lead the AI Architecture Community of Practice to review AI topics with a cross-functional team of stakeholders to ensure compliance with PepsiCo Responsible AI practices and providing coaching and guidance to D AI solution architects Enterprise Architects and program teams on the use of AI capabilities principles and patterns Govern D AI products solution architectures to ensure alignment with AI standards and minimize tech debt maximize reuse and speed to market Work closely with cross-functional teams including AI solutions platforms software development and product management to deliver integrated AI solutions Qualifications Experience Extensive experience in designing developing and deploying AI solutions in a complex enterprise environment Deep understanding of AI ML concepts This includes a strong grasp of ML DL LLM algorithms natural language processing computer vision and other relevant AI technologies Experience with leveraging foundational models from key providers such as OpenAI Azure Google to build LLM enabled applications Experience using popular AI frameworks e g LangGraph LangChain and other AI tools for capabilities such as Agentic flows prompt engineering vector databases and knowledge graphs to build enterprise scale AI enabled applications AI engineering experience applying engineering principles and methodologies to build AI solutions across domains for large multi-country enterprises with complex product lines Knowledge of data engineering principles and best practices for architecting data to enable effective AI solutions and to deliver a data strategy for AI solution training testing and deployment Bachelor s Degree required master s degree preferred Consulting experience building data analytics and AI strategies for clients strongly preferred Experience working in large multinational enterprises with CPG industry experience preferred Experience driving AI technology evaluations across a wide range of vendors using a formal evaluation process Functional Skills Strong understanding and experience with MLOps DLOps and LLMOps frameworks Strong understanding of Responsible AI governance and regulations along with good understanding of security and privacy management ensuring that ethical guidelines and best practices for Responsible AI are followed Ability to collaborate with stakeholders to clearly articulate the value and impact of AI initiatives define the AI strategy and roadmap identifying opportunities for AI integration and innovation Strong analytical and problem-solving abilities to analyze complex problems and develop innovative solutions using AI Desire to proactively stay ahead in the rapidly evolving tech landscape to maintain a competitive edge in the AI domain and stay updated with advancements in generative AI technologies such as transformer-based architecture and diffusion models Systems thinking understanding of relationships between various systems Thorough understanding of the architecture guiding principles modern architecture and leveraging them to design forward-looking solutions Ability to demonstrate a mindset for the Conceptual Logical Physical levels of architecture and apply them effectively Ability to influence senior stakeholders on following technology strategy and solution design for key initiatives to align with standards and architecture guiding principles Ability to balance the long-term big picture and short-term implications of individual decisions Differentiating Competencies Required Demonstrate interest in continuous self-learning and willingness to apply outside in thinking Have obtained professional certifications in AI domain Constantly adaptable to an ever-changing set of priorities Master at the art of influencing to drive alignment at all levels of the organization from development teams on usage of design patterns to Sr VPs on AI tech strategy and solution rationalization Excellent collaboration skills also at all levels of the organization Executive level written verbal communication and presentation skills Ability to turn complex things and diverse data into meaningful insights conclusions and executive messaging Apply proper level of thoroughness and due diligence to architecture recommendations