The posting
Overview Applies knowledge of the Software Engineering area to ensure achievement of key area goals and objectives,leveraging Cloud Technologies and AI-enabled IDEs and agentic development tools to improve engineering productivity. May mentor and/or manage talent to ensure tasks, processes, and projects are completed in an accurate and timely manner, providing direction or support as needed, and guiding teams on the effective use of AI-assisted development and prompt engineering practices. Independently resolves complex problems without clear precedents, requiring extensive investigation and analysis, including using AI-assisted troubleshooting and cloud-based diagnostics. Responsible for programming, configuring, testing and deployment of end-user applications and systems software, including development and deployment on Cloud platforms and integration of Retrieval-Augmented Generation (RAG) and agentic workflow capabilities where applicable. Responsibilities Subject matter expert in the Software Engineering area, influencing stakeholders and applying advanced knowledge to drive achievement of area goals and initiatives; and may mentor and/or oversee associates to guide effective team performance and development, while promoting and enabling the effective use of PepsiCo-approved AI engineering tools to improve team productivity, solution quality, and delivery outcomes. Oversees the design and implementation of software solutions, ensuring alignment with business objectives and user needs, and incorporates AI-enabled development, agentic capabilities, and intelligent automation to enhance scalability, efficiency, and user experience. Directs the regular cadence of software architecture and design reviews to ensure that they stay aligned with organizational standards and goals throughout the end-to-end development process, leveraging AI-assisted code analysis, architecture validation, and automated review capabilities to improve design quality and consistency. Manages the execution of software application strategy, from development to deployment, and ensures consistency with business requirements and performance standards, while utilizing AI-assisted development, testing, and deployment tools to accelerate delivery and improve engineering effectiveness. Strategizes the adoption and integration of new technologies and methodologies to improve software development processes across the organization, including evaluating and enabling the adoption of enterprise-approved AI tools, agentic workflows, and Retrieval-Augmented Generation (RAG) capabilities Leads cross-functional teams to ensure effective collaboration and communication throughout the software development lifecycle, and guides teams in adopting AI-assisted engineering practices and agentic development approaches to enhance productivity and innovation. Collaborates with product management and other stakeholders to gather and prioritize software requirements. Prepares executive reports and briefings on project progress and performance metrics, making recommendations for areas for improvement, including tracking and communicating the impact of AI adoption on engineering productivity, quality, and delivery efficiency. Oversees the execution of key area processes and initiatives, ensuring methods align with the overall functional and business strategy, exercising flexibility to adapt plans as needed, and mentoring colleagues in techniques, processes, and responsibilities, while coaching teams on effective, responsible, and secure use of enterprise-approved AI tools, prompt engineering, and agentic capabilities. Leverages AI-Assisted Agentic IDE coding Tools; ability to generate, validate, and iterate on AI-written code, and guides teams in applying these tools effectively to accelerate development and improve software quality. Basic awareness of agentic workflows — understanding how AI agents chain tasks, and enables teams to configure and utilize agentic workflows to automate engineering and operational processes. Good understanding of foundational AI ethics and exposure to AI-enhanced CI/CD tooling and automated test generation, and ensures teams follow enterprise AI governance, security, and responsible AI usage standards while leveraging AI-enabled engineering capabilities. Qualifications Bachelor’s degree in Computer Science, Engineering, or a related field. A Master’s or PhD in Computer Science or Engineering is preferred. Minimum of 11 years of software development and engineering leadership experience. At least 5 years of experience architecting fault-tolerant, large-scale distributed systems. In-depth knowledge of data structures, algorithms, and object-oriented design. Proficiency in multiple programming languages beyond C#, Java, C, or C++ (for example, Ruby, Python, or Perl). Hands-on experience with cloud platforms (Azure, Google Cloud, AWS) and related PaaS/SaaS solutions. Proven track record working on mission-critical, 24×7 systems. Experience building and maintaining high-throughput, cloud-native distributed systems. Expertise in designing and consuming large-scale web services. Strong understanding of design patterns. Experience with JavaScript/TypeScript, Node.js, and frontend frameworks (e.g., React-Redux). Full-stack engineering experience, demonstrating comfort across both frontend and backend development.
