Lead Software Engineer Artificial Intelligence & Fraud Technology Innovation

Wells Fargo•Woodbridge Township, NJ

3d•$119,000 - $224,000•Onsite

About The Position

About the Role: Wells Fargo is seeking a Lead Software Engineer to join our Fraud and Claims Technology team within the Chief Operating Office (COO) Technology Group. This Lead Software Engineer will drive the design, development, and implementation of innovative Artificial Intelligence (AI) and GenAI technology solutions supporting Fraud and Claims Technology (FCT). FCT delivers innovative technology solutions that support operations, strategic execution, business continuity, regulatory compliance, customer experience, and more—driving modernization and optimization across the enterprise. In this role, you'll work on high-impact products and services that directly influence customer trust and Wells Fargo's bottom line. You'll prototype and test new technologies and solutions, and drive efforts from ideation into the development process, helping to build secure, scalable, efficient, and high-accuracy systems that protect our customers from fraud and disputes. If you're passionate about financial technology, fraud prevention, and AI innovation, this is a unique opportunity to make a meaningful difference.

Requirements

5+ years of Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
5+ years of experience on at least one of the programming language Java/Python/Go Lang
4+ Years of experience in building and maintaining complex technology solutions/data platforms, preferably in financial services or e-commerce

Nice To Haves

Passion for designing and building solutions incorporating AI, machine learning, data science, graph, and/or novel technologies, that deliver a seamless, end-user-focused experience.
Direct experience working within fraud, payments, or online/in-game abuse detection environments is preferred.
Strong expertise in AI model development and deployment with demonstrated hands-on experience in LLMs, generative AI, and AI-engineering.
Experience working with agentic technologies and frameworks.
Working knowledge of AI infrastructure, Generative AI Operations, and enterprise-scale AI adoption strategies.
Experience building solutions and driving development from prototype to production.
Expertise in test or eval driven development, ensuring robust and scalable AI software.
Solid grasp of data and error analysis, identifying issues and patterns throughout the AI pipeline.
Deep experience with generative AI models, including model prompting, tuning, and safety best practices.
Experience in enterprise AI model lifecycle management, AI compliance, and risk mitigation strategies.
Expertise in solution architecture (including front-end, middleware, and backend layers) and applying modular design techniques to workflow automation (including agentic workflow),
Familiarity with enterprise-scale software systems and their integration within large organizations.
Experience in backend application software development, with ability to quickly adapt to C#, and Python code bases.
Excellent collaboration, communication, and problem-solving skills.
Demonstrated success working in dynamic, cross-functional organizations and leading teams and programs via demonstrating technical excellence, coaching, and mentoring.

Responsibilities

Design, prototype, and analyze novel technology solutions (leveraging ML, AI, GenAI, and Agentic AI) to improve fraud detection and prevention capabilities, including capabilities that will be applied across product and operational channels as well as in investigation, analytic, and remediation workflows and environments.
Design, develop and optimize Gen AI applications using agentic frameworks and tools.
Accelerate end-to-end solution delivery timelines by developing automated data, prompting and evaluation pipelines.
Design, test, and refine prompts to optimize AI model performance across various applications, aligning prompts with project goals and user needs through close collaboration with AI developers and product managers.
Stay current with advancements in AI and NLP, incorporating new techniques into prompt engineering.
Collaborate in an Agile environment with architects, developers, and product owners to deliver high-quality solutions.
Promote best practices in software development, architecture, and deployment across environments.
Drive creative improvements to enhance performance, scalability, and maintainability.
Lead projects, teams, and serve as a peer mentor.