Senior AI Research Scientist – Foundation Models & Agentic AI

Wells Fargo•St. Louis, MO

1d•$139,000 - $260,000•Hybrid

About The Position

Wells Fargo’s Model Risk Management team is seeking a Senior Quantitative Analytics Specialist (AI Research Scientist – Foundation Models & Agentic AI - Senior AVP) to support applied research and development in artificial intelligence, focusing on foundation models, agentic AI solutions, and generative AI systems. The role works at the intersection of AI research and financial applications that affect customers. The position involves researching, building, and rigorously evaluating foundation models and agentic AI systems that work with large volumes of structured and unstructured data. The successful candidate will collaborate with researchers, data scientists, applied engineers, and domain experts, and translate research insights into business solutions, open-source contributions, patents, and publications. The role also includes publishing in leading AI/ML conferences and journals and representing Wells Fargo in the broader AI research community. The position has a hybrid work schedule and requires willingness to work onsite at one of the listed locations. It is eligible for visa sponsorship. The posted base pay range is $139,000–$260,000, with possible incentive opportunities. The posting end date is October 25, 2026.

Requirements

At least 4 years of quantitative analytics experience, or equivalent demonstrated through work experience, training, military experience, education, or a combination of these.
A master’s degree or higher in a quantitative discipline such as mathematics, statistics, engineering, physics, economics, or computer science.
Willingness to work onsite at a stated job-posting location.

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 or industry experience.
A strong research track record, including publications in top-tier AI/ML conferences such as NeurIPS, ICML, ICLR, NAACL, or EMNLP, and interest in translating research into real-world applications.
Deep expertise in one or more areas such as foundation models (GPT-4, BERT, LLaMA, Claude), large language models, large reasoning models, multimodal models, or agentic AI.
Ability to apply generative AI or agentic AI throughout the build lifecycle—design, implementation, testing, and iteration—using AI coding copilots such as GitHub Copilot and agentic coding workflows while maintaining enterprise standards.
Hands-on experience with GPU infrastructure, Transformer architecture, and AI/ML tools and frameworks such as TensorFlow, PyTorch, Hugging Face, AWS, and GCP.
Strong engineering background and experience contributing to collaborative software engineering projects, including version control, code reviews, and scalable system design.
Experience transferring foundation models, LLMs, and agentic AI systems into production.

Responsibilities

Conduct highly complex AI, generative AI, agentic AI, and machine-learning research from ideation through experimentation, implementation, evaluation, and documentation.
Explore, apply, and rigorously evaluate emerging AI technologies to develop foundation models and agentic AI systems that address real-world challenges.
Collaborate with researchers, data scientists, applied engineers, and domain experts.
Translate research insights into business solutions, open-source contributions, patents, and publications.
Help build foundation models and agentic AI systems trained on or operating with large volumes of heterogeneous structured and unstructured data to enhance Wells Fargo products, services, and operations.
Publish in top-tier AI/ML conferences and journals and represent Wells Fargo in the broader AI research community.
Follow applicable Wells Fargo risk programs, policies, procedures, and compliance obligations; escalate and remediate issues as required.