Principal Engineer - Java Full Stack-Generative AI, Agentic AI

About this role: Wells Fargo is seeking a Principal Engineer to provide enterprise-level technical leadership for the architecture, design, engineering, and modernization of mission-critical Financial Crimes and Risk Management platforms.  In this role, you will: Act as an advisor to leadership to develop or influence applications, network, information security, database, operating systems, or web technologies for highly complex business and technical needs across multiple groups Lead the strategy and resolution of highly complex and unique challenges requiring in-depth evaluation across multiple areas or the enterprise, delivering solutions that are long-term, large-scale and require vision, creativity, innovation, advanced analytical and inductive thinking Translate advanced technology experience, an in-depth knowledge of the organizations tactical and strategic business objectives, the enterprise technological environment, the organization structure, and strategic technological opportunities and requirements into technical engineering solutions Provide vision, direction and expertise to leadership on implementing innovative and significant business solutions Maintain knowledge of industry best practices and new technologies and recommends innovations that enhance operations or provide a competitive advantage to the organization Strategically engage with all levels of professionals and managers across the enterprise and serve as an expert advisor to leadership Required Qualifications: 7+ years of Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education Desired Qualifications  Strong hands-on experience in Java ecosystem technologies, including Core Java, Spring Boot, REST APIs, microservices, concurrency, and performance optimization.  Strong experience in frontend architecture and development using React or Angular, JavaScript or TypeScript, HTML, and CSS, with the ability to build secure, accessible, resilient, and scalable enterprise user experiences.  Proven experience designing, building, modernizing, and operating large-scale distributed systems in production.  Strong understanding of object-oriented design, domain-driven design, microservices architecture, API design, event-driven systems, integration patterns, and distributed computing.  Hands-on experience delivering Generative AI solutions using large language models, retrieval-augmented generation, embeddings, vector databases, prompt engineering, evaluation approaches, and agent orchestration frameworks.  Experience integrating AI capabilities into enterprise platforms, backend services, digital workflows, and engineering processes in a secure, resilient, governed, and supportable manner.  Experience defining architecture and integration patterns for machine learning-enabled systems, model services, data pipelines, and scalable deployment.  Experience with cloud-native architecture, containers, orchestration platforms, infrastructure automation, CI/CD, DevSecOps, observability, and site reliability engineering practices.  Experience designing highly available and resilient systems with appropriate recovery, fault-tolerance, capacity, performance, monitoring, and operational-support patterns.  Demonstrated ability to identify and eliminate redundant technologies, overlapping capabilities, duplicate solutions, and fragmented engineering patterns across multiple domains.  Experience creating reusable platforms, common services, reference architectures, accelerators, or engineering frameworks that can be adopted by multiple teams.  Demonstrated curiosity about emerging technology concepts and the ability to evaluate their practical application to business problems.  Awareness of emerging areas such as digital assets, harness engineering, loop engineering, newer AI models, intelligent automation, modern data platforms, and next-generation development