Lead Artificial Intelligence Solutions Consultant

About this role:

Wells Fargo is seeking a Lead Use Case Discovery Consultant to join our new team. The Use Case Discovery organization is part of the Enterprise Gen AI organization. It is tasked to identify big Gen AI use cases that will have huge impacts and can potentially change how Wells Fargo does business. The ideal candidate will have a good understanding of artificial intelligence (AI) technologies, particularly generative AI, and will be adept at identifying and developing innovative use cases to leverage these technologies within various business environments

In this role, you will:

• Develop Use Cases: Conceptualize and create detailed use cases for generative AI applications across different industries.
• Understand Current Inventory: Evaluate the existing inventory of AI use cases within the organization.
• Collaborate with Leaders: Work closely with Line of Business (LOB) leaders to ideate and conceptualize generative AI applications that can address specific business needs. Help the partners identify opportunities where generative AI can add value
• Analyze Impact: Understand and articulate the potential impact of proposed AI applications on business processes and outcomes.
• Align with Strategy: Recognize and ensure alignment of AI use cases with the overall enterprise strategy and goals.
• Prioritize Use Cases: Help prioritize AI use cases based on their feasibility, impact, and strategic importance.
• Collaborate with Stakeholders: Work closely with business leaders, technical teams, and external partners to gather requirements and validate use cases.
• Stay Updated: Keep abreast of the latest advancements in AI and emerging technologies to continuously refine use case strategies.
• Report and Present Findings: Prepare comprehensive reports and presentations to communicate findings and recommendations to stakeholders.

Required Qualifications:

• 5+ years of Artificial Intelligence Solutions experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education

Desired Qualifications:

• Experience in Artificial Intelligence Solutions, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
• Education: Bachelor's degree in Computer Science, Engineering, or a related field. A Master’s degree AI or Machine Learning is preferred.
• Technical Skills: Proficiency in AI/ML, Agentic frameworks and programming languages (e.g., Python).
• Analytical Skills: Strong analytical and problem-solving capabilities, with the ability to translate business needs into technical solutions.
• Communication Skills: Excellent written and verbal communication skills, with the ability to articulate complex ideas to diverse audiences.

Job Expectations:

• Ability to work a hybrid schedule

• Relocation assistance is not available for this position
• This position is not eligible for Visa sponsorship

Posting End Date: 

9 Jul 2025

*Job posting may come down early due to volume of applicants.

We Value Equal Opportunity

Wells Fargo is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other legally protected characteristic.

Employees support our focus on building strong customer relationships balanced with a strong risk mitigating and compliance-driven culture which firmly establishes those disciplines as critical to the success of our customers and company. They are accountable for execution of all applicable risk programs (Credit, Market, Financial Crimes, Operational, Regulatory Compliance), which includes effectively following and adhering to applicable Wells Fargo policies and procedures, appropriately fulfilling risk and compliance obligations, timely and effective escalation and remediation of issues, and making sound risk decisions. There is emphasis on proactive monitoring, governance, risk identification and escalation, as well as making sound risk decisions commensurate with the business unit’s risk appetite and all risk and compliance program requirements.