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 practices.
• Experience working in Financial Crimes, Risk Management, banking, financial services, or another highly regulated environment.
• Understanding of regulatory, security, privacy, model risk, data governance, audit, resiliency, and operational-risk considerations relevant to enterprise technology solutions.
• Ability to connect engineering decisions to business results, customer outcomes, regulatory obligations, risk reduction, operational efficiency, …