We are pepsico join pepsico and dare for better! Being part of pepsico means being part of one of the largest food and beverage companies in the world, with our iconic brands consumed more than a billion times a day in more than 200 countries. Our product portfolio, which includes 22 of the world's most iconic brands, such as sabritas, gamesa, quaker, pepsi, gatorade and sonrics, has been a part of mexican homes for more than 116 years.the ai/ml architect is responsible for designing, developing, and implementing advanced ai-driven conversational and agentic solutions using azure, aws or custom developed ai services, cutting-edge language models, and modern programming languages such as python and java. This role demands deep expertise in natural language processing (nlp), dialog management, agent orchestration, and cloud-native ai deployments to create seamless, intelligent, and scalable conversational experiences and autonomous agents.develop comprehensive dialog flows, intent recognition models, entity extraction, and sentiment analysis for complex conversational interactions. • architect agentic systems, focusing on planning, reasoning, and execution, integrating tools and apis for autonomous task completion. • cloud & infrastructure development (focused on conversational & agentic ai): • design and deploy scalable and resilient cloud infrastructure for conversational and agentic ai applications on azure or aws, leveraging native ai services, azure copilot studio or aws lex & connect, azure ml / aws sagemaker, and llm services like openai / bedrock. • design and deploy multiple ai agents using open source development, deployment and orchestration frameworks like langgraph and crew.ai or their commercial equivalent. • optimize cloud resources for efficient processing of natural language queries, llm inferences, and agentic workflows. • implement serverless architectures and containerized solutions (docker, kubernetes) for deploying and managing conversational and agentic ai models. Database & knowledge engineering (focused on conversational & agentic ai): • design and implement knowledge graphs and vector databases (e.g., azure cognitive search, pinecone, weaviate) to support conversational and agentic ai systems. • develop data pipelines for ingesting, processing, and storing conversational data, including transcripts, user interactions, and knowledge base content. • implement data retrieval and augmentation strategies, including retrieval augmented generation (rag) to enhance the accuracy and relevance of conversational and agentic responses. Integration & deployment (focused on conversational & agentic ai): • integrate conversational and agentic ai solutions with various channels, including web, mobile, messaging platforms (sms, whatsapp, etc.), social media (facebook messenger, ticktock, etc.) Implement ci/cd pipelines for automated deployment and testing of conversational and agentic ai models and applications. Performance optimization & governance (focused on conversational & agentic ai): • monitor and optimize the performance of conversational and agentic ai systems, including response latency, accuracy, and user satisfaction. • implement robust testing and evaluation frameworks for conversational and agentic ai models, including a/b testing and user feedback analysis. • ensure compliance with data privacy and security regulations for conversational and agentic ai applications. • collaborate with product managers, data scientists, and engineers to define and deliver conversational and agentic ai solutions. • provide technical guidance and mentorship to junior team members on conversational and agentic ai development. Bachelor's or master's degree in computer science, ai, natural language processing, or a related field.strong proficiency in python, with experience in nlp libraries (e.g., cloud technologies: deep expertise in azure and/or aws with focus on ai services (e.g., azure cognitive services), openai or bedrock apis, azure machine learning or aws sagemaker, and azure copilot studio or aws lex+connect with a focus on conversational and agentic ai. • database technologies: hands-on experience with vector databases (e.g., azure cognitive search, pinecone, weaviate), sql, and nosql databases. • strong understanding of intent recognition, entity extraction, and sentiment analysis. • understanding of planning and reasoning in ai. • mlops & devops: proficiency in ci/cd pipelines, docker, kubernetes, and model deployment workflows for conversational and agentic ai. • internal digital platforms that promote self-learning. Specialized training according to the role. Financial wellness programs that will help you reach your goals in all stages of life we are an equal opportunity employer and value diversity at our company. We respect and value diversity as a work force and innovation for the organization.