Lead Specialty Software Engineer - AI Enginnering

Wells Fargo•St. Louis, MO

1d•$159,000 - $305,000•Hybrid

About The Position

About This Role: Wells Fargo is seeking a Lead Specialty Software Engineer – AI Engineering to drive the development and integration of AI‑powered solutions across complex, business‑critical systems. This role combines hands‑on engineering with technical leadership, mentoring, and cross‑team collaboration. The ideal candidate will have strong experience in backend and frontend development, modern AI/Generative AI frameworks, and a proven ability to lead initiatives while ensuring operational excellence, risk management, and regulatory compliance. In This Role, You Will Lead complex technical initiatives within assigned domains, delivering scalable and resilient AI‑enabled solutions Design, develop, test, and implement applications, system components, tools, utilities, and services leveraging modern technologies Build and integrate AI and Generative AI capabilities into enterprise applications, including LLM‑driven features Ensure systems are effectively monitored to improve operational efficiency and proactively mitigate risk Identify opportunities to optimize resource utilization, enhance processes, and reduce operational costs Troubleshoot and resolve complex coding, testing, and escalated platform issues Lead teams to ensure compliance with security, risk, and regulatory requirements, and partner with stakeholders to implement key risk initiatives Mentor and coach less experienced software engineers, promoting best practices and technical growth Collaborate with and influence stakeholders across engineering, product, platform, and production support teams Lead teams to successfully meet project objectives, milestones, and delivery expectations Partner closely with production support and platform engineering teams to ensure system stability and continuity

Requirements

5+ years of Specialty Software Engineering experience, or equivalent demonstrated through work experience, training, education, or military service
2+ years of hands‑on experience developing backend applications using Python and/or Java, including RESTful services and frameworks such as Spring Boot
2+ years of experience building modern user interfaces or chatbot applications using React and/or Angular, with a solid understanding of component‑based architecture
2+ years of experience working with AI or Generative AI frameworks (e.g., LangChain, LangGraph) to build or integrate AI‑enabled application features

Nice To Haves

Experience participating in LLM evaluation or validation activities, including testing, quality assessment, or performance analysis of model outputs
Demonstrated knowledge of prompt engineering techniques, including prompt design, experimentation, iteration, and optimization
Practical experience using AI‑assisted development tools (e.g., GitHub Copilot) to improve developer productivity and code quality
Experience contributing to reusable components, libraries, or shared frameworks within an enterprise application environment
Familiarity with AI observability, evaluation, or monitoring tools to support reliability, performance, and governance

Responsibilities

Lead complex technical initiatives within assigned domains, delivering scalable and resilient AI‑enabled solutions
Design, develop, test, and implement applications, system components, tools, utilities, and services leveraging modern technologies
Build and integrate AI and Generative AI capabilities into enterprise applications, including LLM‑driven features
Ensure systems are effectively monitored to improve operational efficiency and proactively mitigate risk
Identify opportunities to optimize resource utilization, enhance processes, and reduce operational costs
Troubleshoot and resolve complex coding, testing, and escalated platform issues
Lead teams to ensure compliance with security, risk, and regulatory requirements, and partner with stakeholders to implement key risk initiatives
Mentor and coach less experienced software engineers, promoting best practices and technical growth
Collaborate with and influence stakeholders across engineering, product, platform, and production support teams
Lead teams to successfully meet project objectives, milestones, and delivery expectations
Partner closely with production support and platform engineering teams to ensure system stability and continuity