AI Solutions Consultant
Wells Fargo
Charlotte, NC, US
Onsite
2026-07-01
Estimated salary · Charlotte
~ $67,900 - $125,400
Low
$67K
Median
$93K
High
$125K
Market in Charlotte · BLS OEWS 2025
Estimated net pay
$4,533 - $7,707
/month · 20% withheld
after tax & contributions · on the estimated salary · Single, no dependents
Job description
**About this role:**
Wells Fargo Digital Data and AI organization within Consumer banking and Lending is seeking an AI Solutions Consultant \- Conversational Architect to plan and implement advanced conversational experiences on our Virtual Assistant platforms, reaching over 30 million Wells Fargo customers.
Learn more about the career areas and lines of business at wellsfargojobs.com.
**In this role, you will:**
* Partner with various partners including PM’s, PO’s, UX designers and content strategist to plan, validate and execute the model and implementation of GenAI experiences within the virtual assistant
* Build the business rules, logic and API interactions that are required for sophisticated interactions
* Deploy GenAI innovations to enable more complex conversations using the latest build patterns including RAG, agentic, multi\-agent orchestration, and tool calling
* Work closely with other members of the product team and technology partners to identify enhancements to the conversational experiences
* Act as a liaison between our AI Product team and Technology to ensure that our Virtual Assistant delivers intelligent and intuitive conversations, resulting in a great customer experience
**Required Qualifications:**
* 2\+ years of AI Solutions experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
* 2\+ years experience developing and deploying conversational virtual assistants
* 2\+ years hands\-on experience utilizing conversational AI platforms or orchestration frameworks such as LangGraph or ADK, with preference given for Google Dialogflow CX, Conversational Agents, CX Agent Assist
* 2\+ years hands\-on experience building GenAI applications using Large Language Models (LLMs) and Retrieval\-Augmented Generation (RAG) architectures including setting up vector databases and prompt engineering
* Knowledge and understanding of GenAI\-related skills such as chunking a
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