Senior Lead AI Research Scientist – Foundation Models & Agentic AI

Wells Fargo & Company•Irving, TX

1d•$185,000 - $300,000•Hybrid

About The Position

Wells Fargo’s Model Risk Management (MRM) team is seeking a Senior Lead Quantitative Analytics Specialist (AI Research Scientist Lead – Foundation Models & Agentic AI) to drive advanced AI initiatives. This role will lead the development and evaluation of next-generation Foundation Models, Agentic AI solutions, and Generative AI systems, ensuring they are robust, scalable, and aligned with regulatory expectations. This is a high-impact opportunity to operate at the intersection of AI innovation and model risk oversight, partnering with business, technology, and risk leaders to bring cutting-edge AI capabilities into real-world financial applications that serve millions of customers.

Requirements

7+ years of Quantitative Analytics experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
Master's degree or higher in a quantitative discipline such as mathematics, statistics, engineering, physics, economics, or computer science

Nice To Haves

PhD in Computer Science, Artificial Intelligence, or a closely related computational field, or an MSc with at least 3 years of relevant applied research / research innovation or industry experience building foundational models.
Solid proven research track record with publications in top-tier AI/ML conferences such as NeurIPS, ICML, ICLR, NAACL, or EMNLP, combined with a demonstrated interest in translating research into real-world applications that impact millions of customers.
Deep expertise in one or more specialized areas, including but not limited to: Foundation Models (GPT-4, BERT, LLaMA, Claude), Large Language Models (LLMs), Large Reasoning Models, Multimodal Models, Agentic AI
Demonstrated ability to apply GenAI / Agentic AI in the full build lifecycle - design, implementation, testing, and iteration - leveraging AI coding copilots (e.g., GitHub Copilot) and agentic coding workflows to accelerate delivery while maintaining enterprise standards
Hands-on experience with GPU infrastructure, Transformer architecture, modern AI/ML development frameworks and tools such as TensorFlow, PyTorch, Hugging Face, AWS, GCP.
Strong engineering background with demonstrated ability to contribute to collaborative software engineering projects, including version control, code reviews, and scalable system design.
Experience with transferring foundation models, LLMs, and agentic AI systems in production

Responsibilities

Lead end-to-end research projects in Agentic AI / AI / Generative AI / Machine Learning from ideation, research, experimentation, implementation, evaluation, transfer and documentation.
Contribute and lead building the next generation of foundation models and agentic AI systems trained / operating on large volumes of heterogeneous data - both structured and unstructured - that enhance Wells Fargo's products, services, and operations.
Lead the deployment of foundation models, LLMs, and agentic AI systems into production, with a strong understanding of deployment trade-offs.
Drive the exploration, application, and rigorous evaluation of emerging AI technologies that solve real-world challenges.
Collaborate closely with interdisciplinary teams, including researchers, data scientists, applied engineers, and domain experts.
Translate research insights into impactful business solutions, open-source contributions, patents, and publications.
Publish in top-tier AI/ML conferences and journals and represent Wells Fargo in the broader AI research community.