Lead Software Engineer - Java & AI

About this role:
Wells Fargo is seeking a Lead Software Engineer with strong hands-on experience in Java full-stack development, Spring Boot, microservices, APIs, modern UI technologies, and AI-enabled software engineering.
The role will provide hands-on technical leadership across application design, development, testing, deployment, and production support. The engineer will also help drive adoption of Generative AI and AI-assisted development tools such as GitHub Copilot, Microsoft Copilot, Devin AI, and other emerging engineering tools to improve developer productivity and software quality.
In this role, you will:

• Lead complex technology initiatives including those that are companywide with broad impact
• Act as a key participant in developing standards and companywide best practices for engineering complex and large scale technology solutions for technology engineering disciplines
• Design, code, test, debug, and document for projects and programs
• Review and analyze complex, large-scale technology solutions for tactical and strategic business objectives, enterprise technological environment, and technical challenges that require in-depth evaluation of multiple factors, including intangibles or unprecedented technical factors
• Make decisions in developing standard and companywide best practices for engineering and technology solutions requiring understanding of industry best practices and new technologies, influencing and leading technology team to meet deliverables and drive new initiatives
• Collaborate and consult with key technical experts, senior technology team, and external industry groups to resolve complex technical issues and achieve goals
• Lead projects, teams, or serve as a peer mentor

Required Qualifications:

• 5+ years of Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education

Desired Qualifications:

• Technical Leadership: Lead the design and development of complex enterprise applications using Java, Spring Boot, microservices, REST APIs, and modern web technologies.
• Design scalable, secure, highly available, and maintainable application architectures.
• Provide hands-on technical leadership throughout the software development lifecycle, including design, coding, testing, deployment, troubleshooting, and production support.
• Develop reusable services, APIs, frameworks, and application components that improve engineering productivity and consistency.
• Build modern user experiences using technologies such as React, Angular, JavaScript/TypeScript, HTML and CSS.
• Design and develop RESTful APIs, microservices and event-driven applications using technologies such as Spring Boot and Kafka.
• Apply appropriate software design patterns, domain-driven design principles, API standards, and engineering best practices.
• Conduct code reviews, design reviews and technical walkthroughs, identifying opportunities to improve performance, maintainability, security and code quality.
• Troubleshoot complex application, integration, performance and production issues and drive them to resolution.
• Champion automated testing, CI/CD, DevSecOps and engineering automation across the software development lifecycle.
• Work with relational and NoSQL databases and develop efficient data-access and integration patterns.
• Collaborate with Product, Architecture, Information Security, Infrastructure and other engineering teams to translate business requirements into technical solutions.
• Evaluate emerging technologies through technical assessments, prototypes and proof-of-concepts.

• AI & Modern Software Engineering: Apply Generative AI and AI-assisted development techniques across the software engineering lifecycle.
• Use AI coding assistants such as GitHub Copilot, Microsoft Copilot, Devin AI, and similar tools to improve developer productivity while following enterprise security, privacy and software engineering standards.
• Identify opportunities to use AI for code generation, code understanding, unit testing, documentation, refactoring, debugging and developer productivity.
• Design and develop applications that integrate with Large Language Models (LLMs) and Generative AI capabilities.
• Develop practical understanding of prompt engineering, RAG, vector databases, embeddings, AI agents, MCP servers and Agent-to-Agent (A2A) concepts.
• Build or contribute to AI-powered applications and intelligent workflows using enterprise-approved AI platforms and APIs.
• Evaluate AI-generated code for correctness, security, performance, maintainability and compliance rather than relying on AI-generated output without engineering review.
• Explore emerging agentic software engineering approaches and automation opportunities that can accelerate application development, testing and maintenance.
• Help establish engineering practices for the responsible and secure adoption of AI-assisted development tools.
• Engineering Leadership: Serve as a technical lead and hands-on engineer, providing technical direction to software engineering teams.
• Mentor Software Engineers and Senior Software Engineers on Java, Spring Boot, application architecture, design patterns and modern engineering practices.
• Provide guidance on complex design, coding and troubleshooting challenges.
• Drive engineering excellence through clean code, automated testing, reusable components, automation and continuous improvement.
• Facilitate design reviews, code reviews, technical discussions and knowledge-sharing sessions.
• Encourage engineers to experiment with and responsibly adopt new AI and developer productivity tools.
• Partner with Product Owners and other stakeholders to understand requirements, identify technical dependencies and support delivery planning.
• Provide technical estimates and identify engineering risks, dependencies and implementation options.
• Demonstrate ownership beyond individual assignments and help the broader engineering team achieve technology and business outcomes.

Job Expectations:

• Bachelor's degree in engineering, Computer Science or equivalent practical experience.
• Strong hands-on software engineering experience developing enterprise-scale applications.
• Strong hands-on development experience with Java and Spring Boot.
• Experience designing and developing microservices and REST APIs.
• Experience with Spring ecosystem technologies, including Spring Boot, Spring MVC, Spring Data and Spring Security.
• Experience with front-end technologies such as React or Angular, JavaScript/TypeScript, HTML and CSS.
• Strong understanding of object-oriented programming, design patterns, data structures and software engineering principles.
• Experience applying AI/GenAI capabilities to real-world software engineering or business use cases.
• Experience with relational databases such as Oracle, PostgreSQL or SQL Server, along with strong SQL skills.
• Experience with distributed technologies and messaging platforms such as Kafka.
• Experience with automated testing frameworks including JUnit, Mockito, Selenium or comparable technologies.
• Strong understanding of CI/CD, Git, Maven/Gradle, SonarQube and artifact management.
• Experience with containerized application platforms such as Kubernetes or OpenShift/OCP.
• Working knowledge of public cloud platforms such as GCP or Azure, particularly for deploying and operating modern applications.
• Understanding of Generative AI, Large Language Models and AI-assisted software engineering.
• Experience using or evaluating AI coding assistants and developer productivity tools.
• Ability to perform code reviews, solution design reviews, debugging and troubleshooting of complex enterprise applications.
• Strong verbal, written and interpersonal communication skills.
• Ability to work effectively in an Agile environment using Scrum or Kanban.
• Demonstrated ability to mentor engineers and provide technical leadership without requiring direct people-management responsibility.

Posting End Date:
18 Nov 2026
*Job posting may come down early due to volume of applicants.
We Value Equal Opportunity
Wells Fargo is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other legally protected characteristic.
Employees support our focus on building strong customer relationships balanced with a strong risk mitigating and compliance-driven culture which firmly establishes those disciplines as critical to the success of our customers and company. They are accountable for execution of all applicable risk programs (Credit, Market, Financial Crimes, Operational, Regulatory Compliance), which includes effectively following and adhering to applicable Wells Fargo policies and procedures, appropriately fulfilling risk and compliance obligations, timely and effective escalation and remediation of issues, and making sound risk decisions. There is emphasis on proactive monitoring, governance, risk identification and escalation, as well as making sound risk decisions commensurate with the business unit's risk appetite and all risk and compliance program requirements.
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