Senior Lead AI Research Scientist - Foundation Models & Agentic AI
Role details
Job location
Tech stack
Job description
- 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.
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, * 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
Benefits & conditions
Wells Fargo provides eligible employees with a comprehensive set of benefits, many of which are listed below. Visit Benefits - Wells Fargo Jobs (https://www.wellsfargojobs.com/en/life-at-wells-fargo/benefits) for an overview of the following benefit plans and programs offered to employees.
- Health benefits
- 401(k) Plan
- Paid time off
- Disability benefits
- Life insurance, critical illness insurance, and accident insurance
- Parental leave
- Critical caregiving leave
- Discounts and savings
- Commuter benefits
- Tuition reimbursement
- Scholarships for dependent children
- Adoption reimbursement
Posting End Date:
28 Jun 2026
***** 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.