Senior Lead Artificial Intelligence Solutions Consultant - Data Science/Risk Management Consultant

Wells Fargo Bank • Charlotte, NC

13d • Hybrid

About The Position

Why Wells Fargo Are you looking for more? Find it here. At Wells Fargo, we're more than a financial services leader – we’re a global trailblazer committed to driving innovation, empowering communities, and helping our customers succeed. We believe that a meaningful career is much more than just a job – it’s about finding all of the elements to help you thrive, in one place. Living the Well Life means you’re supported in life, not just work. It means having robust benefits, competitive compensation, and programs designed to help you find work-life balance and well-being. You’ll be rewarded for investing in your community, celebrated for being your authentic self, and empowered to grow. Join us! About this role: Wells Fargo is seeking a Senior Lead Artificial Intelligence Solutions Consultant specializing in Data Science – Model Risk management, Generative AI (Gen-AI) , Agentic AI solutions to drive innovation while ensuring robust governance and compliance. This role requires expertise in building and fine-tuning custom Small Language Models (SLMs) for specific business applications, implementing robust evaluation frameworks, and ensuring compliance with enterprise risk governance standards. The ideal candidate will also possess deep knowledge of prompt engineering concepts and strategies to optimize AI performance and reliability. In this role, you will:

Requirements

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

Nice To Haves

• Experience with Data Science , quantitative modeling , and model risk management .
• Deep experience with Gen-AI and Agentic AI solutions design, model development and validation.
• Hands-on experience with Generative AI ( LLMs , NLP, diffusion models , etc.) and Agentic AI architectures (autonomous/multi-agent systems).
• Ability to build and optimize custom Small Language Models (SLMs) for enterprise-grade solutions.
• Proven expertise in model fine-tuning and domain adaptation for business-specific applications.
• Strong knowledge of prompt engineering principles, including prompt design, chaining, and optimization for LLMs , NLP and SLMs .
• Certifications in AI Governance, Risk Management, or Responsible AI preferred.
• Advanced degree (MS/PhD) in Data Science, Machine Learning, Statistics, or related field preferred.

Responsibilities

• Strategic Advisory – Act as an advisor to senior leadership. Develop or influence objectives, plans, specifications, resources, and long-term goals for highly complex business and technical needs that can be resolved through utilizing data-driven advanced analytical, statistical techniques, algorithms, or models.
• Cross-Functional Collaboration – Align AI solutions with governance. Collaborate with cross-functional teams—data scientists, risk managers, compliance officers—to align AI solutions with governance frameworks.
• Responsible AI Leadership – Promote ethical and transparent practices. Provide thought leadership on responsible AI practices, including transparency, accountability, and ethical considerations.
• Custom Model Development – Optimize domain-specific SLMs. Design, fine-tune, and optimize custom SLMs for domain-specific business use cases, ensuring alignment with operational and compliance requirements.
• Prompt Engineering – Enhance model accuracy and efficiency. Develop prompt engineering strategies to enhance model accuracy, contextual relevance, and efficiency across diverse applications.
• Model Validation – Ensure reliability through rigorous testing. Validate and benchmark AI models using advanced statistical techniques, stress testing, and drift detection methodologies.
• Risk Assessment – Evaluate fairness and robustness. Conduct model risk assessments focusing on fairness, explainability, robustness, and ethical compliance.
• Governance Documentation – Support regulatory compliance. Gather and document evidence for Model Risk Governance (MRG) submissions, ensuring adherence to regulatory and internal standards.
• Evaluation Pipelines – Monitor AI lifecycle performance. Build evaluation pipelines for Generative and Agentic AI systems, including lifecycle monitoring and performance audits.
• Regulatory Alignment – Partner for compliant AI deployments. Partner with technology and legal teams to ensure AI deployments meet enterprise risk and regulatory expectations.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed
• Number of Employees: 5,001-10,000 employees