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Wells Fargo is seeking a Lead Software Engineer to join our team to drive digital transformation. We believe in the power of collaboration—great ideas can come from anyone, and every employee has the opportunity to make a meaningful impact. Through teamwork and shared innovation, we drive outcomes that matter for our customers and the company. Explore career opportunities with Wells Fargo and be part of a supportive, inclusive environment where you can learn, grow, and build solutions that make a difference.
Job Responsibility:
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
Requirements:
5+ years of Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
Proven hands-on software development expertise in designing and delivering high‑performance, large‑scale, distributed applications
3+ Years of experience in building AI/GenAI solutions driving innovation
Strong background in AI, Machine Learning, GenAI, or Data Science, including retrieval systems, embeddings, chunking strategies, and agentic AI workflows
Proven hands-on experience building and deploying AI-powered applications in enterprise environments, including RAG, LLM APIs, and low-code GenAI solutions (Copilot Studio or equivalent)
Strong understanding of LLM evaluation metrics, golden dataset design, faithfulness/grounding checks, hallucination scoring, and automated model-graded evaluations
Experience implementing observability and monitoring for AI systems (logs, traces, metrics, token usage, latency, and error tracking)
Proven ability to drive cross-functional programs and influence senior stakeholders
Ensure responsible AI and security controls—guardrails, PII filtering, DLP, red-teaming, and safe deployment practices
Strong understanding of AI and ML algorithms, spanning supervised/unsupervised learning, deep learning, transformers, optimization methods, and practical application of these techniques in production systems
4+ years experience using Git or other version control systems
Nice to have:
Experience with low-code / enterprise platforms such as Copilot Studio, Power Platform, or Agent Space
Knowledge in Vector database , chunking and embedding models
Hands-on knowledge of LangChain, LangGraph, or other agent orchestration frameworks
Strong understanding of Risk Management, Controls, Testing & Monitoring, or governance frameworks within corporate risk environments
Proficiency in Python coding , NodeJS
Experience in design, code, test, debug, and documentation for projects and programs associated with technology domain, including upgrades and deployments