Lead Specialty AI Java Software Engineer

Wells Fargo•Charlotte, NC

1d•Hybrid

About The Position

Wells Fargo is seeking a Lead Specialty AI Java Software Engineer in Technology as part of Commercial and Corporate & Investment Banking Technology (CCIBT). This role is crucial for building next-generation solutions for the Wells Fargo Capital Markets Technology organization, focusing on automation, AI adoption, and platform modernization. The engineer will build and evolve strategic trading analytics data platforms, including the Low Touch Data Hub and the next-generation Equities Data & Analytics platform supporting all Equities Front Office trading groups. The position involves contributing to the design and delivery of scalable application frameworks and data services within Commercial and Corporate & Investment Banking Technology, enabling advanced analytics, AI-driven insights, and automation across the Equities trading lifecycle. This role defines and governs enterprise-standard AI-assisted engineering patterns, including prompt-driven development, automated testing, diagnostics, documentation, and developer-productivity tooling. You will architect and guide controlled LLM integrations, such as MCP-based services, across development workflows, observability, and automation, while establishing guardrails to ensure secure, explainable, auditable, and compliant AI usage within electronic trading technology. In partnership with platform, security, risk, and compliance teams, you will ensure AI-enabled engineering practices meet Wells Fargo governance standards and continuously evaluate advances in GenAI, agentic AI, and applied ML to safely evolve engineering capabilities at enterprise scale. This role supports a fast-paced Front Office equities trading environment, delivering senior-level software and analytics solutions for trading, automation, and decisioning. You will build AI-enabled analytics platforms and low-latency systems, apply AI-centric engineering practices, and write high-quality Java and Python code while partnering closely with traders, Strats, and quants.

Requirements

5+ years of Specialty Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
5+ years of Software Engineering experience, with a strong focus on data-intensive systems
5+ years of experience building analytics platforms, data services, or data-driven applications
5+ years of experience with algorithms and data structures, particularly as applied to analytics and data processing
4+ years of experience designing and implementing distributed data systems
4+ years of experience with time-series, relational, or analytical databases
4+ years of experience in Java for building high-performance backend and data services
4+ years of experience in Python for analytics, data processing, and automation

Nice To Haves

Advanced experience in capital markets business processes
Working knowledge of SEC, FINRA, and international regulatory considerations when building technology solutions
Cash Equities and Global Markets trading workflow knowledge; FIX protocol experience
Deep understanding of concurrency, memory management, and performance tuning in data-heavy systems
Experience with application lifecycle management from design through production support, including AI-enabled or analytics-driven systems
Strong understanding of distributed and client-server technology architectures
Prior team lead and/or direct or matrix management experience
Outstanding written and verbal communication skills appropriate for a Front Office environment
BS/BA degree or higher

Responsibilities

Lead complex initiatives on selected domains
Ensure systems are monitored to increase operational efficiency and managed to mitigate risk
Define opportunities to maximize resource utilization and improve processes while reducing cost
Lead, design, develop, test and implement applications and system components, tools and utilities, models, simulation, and analytics to manage complex business functions using sophisticated technologies
Resolve coding, testing and escalated platform issues of a technically challenging nature
Lead team to ensure compliance and risk management requirements for supported area are met and work with other stakeholders to implement key risk initiatives
Mentor less experienced software engineers
Collaborate and influence all levels of professionals including managers
Lead team to achieve objectives
Partner with production support and platform engineering teams effectively
Technical leadership
Rigorous testing and reviews
Production reliability ownership
Level-2 support for performance, data, and model-driven issues