Principal AI Research Scientist

At U.S. Bank, we’re on a journey to do our best. Helping the customers and businesses we serve to make better and smarter financial decisions and enabling the communities we support to grow and succeed. We believe it takes all of us to bring our shared ambition to life, and each person is unique in their potential. A career with U.S. Bank gives you a wide, ever-growing range of opportunities to discover what makes you thrive at every stage of your career.

Try new things, learn new skills and discover what you excel at—all from Day One.

U.S. Bank is seeking a Principal AI Research Scientist to join the Artificial Intelligence Center of Excellence (AI CoE), a high-impact organization responsible for advancing the bank’s AI strategy from early-stage research through enterprise deployment.

This role is ideal for a highly technical and hands‑on AI leader who thrives at the intersection of research, innovation, and execution. The successful candidate will continuously evaluate emerging advances in artificial intelligence, identify opportunities to create business value, rapidly prototype novel solutions, and lead their evolution into scalable enterprise capabilities.

Unlike traditional research positions, this role spans the entire R&D lifecycle. The ideal candidate combines deep scientific expertise with strong software engineering and solution delivery capabilities, enabling them to move seamlessly from research exploration and experimentation to deployment and adoption of production‑grade AI solutions.

The candidate is expected to be an active contributor to the broader AI community, maintain awareness of cutting‑edge academic and industry developments, and help shape the future direction of AI innovation within the bank.

AI Research & Innovation

• Monitor, evaluate, and experiment with emerging AI technologies, research breakthroughs, and industry trends, with particular emphasis on generative AI, large language models (LLMs), multimodal AI, and agentic AI systems.
• Identify opportunities to apply advanced AI techniques to complex business problems across financial services.
• Conduct original AI research and exploratory investigations to assess the feasibility and value of novel approaches.
• Develop hypotheses, design experiments, evaluate results, and communicate findings to technical and executive stakeholders.
• Contribute to publications, patents, technical whitepapers, and thought leadership initiatives where appropriate.

Prototyping & Solution Development

• Rapidly transform research concepts into working prototypes and proof‑of‑concepts.
• Design, develop, and validate AI solutions across the full lifecycle, from data preparation and modeling through deployment and monitoring.
• Build experimental and production‑ready solutions using modern AI/ML tools, frameworks, and cloud platforms.
• Apply best practices in model evaluation, benchmarking, explainability, security, and responsible AI.

Generative AI & Agentic Systems

• Lead the development of solutions leveraging foundation models, generative AI, retrieval‑augmented generation (RAG), fine‑tuning techniques, and agentic workflows.
• Design and evaluate AI agents, multi‑agent systems, orchestration frameworks, tool‑use architectures, memory systems, and human‑in‑the‑loop workflows.
• Establish best practices for prompt engineering, model adaptation, evaluation, observability, and governance of LLM‑based systems.
• Assess emerging model architectures and determine their applicability within a highly regulated environment.

Deployment & Technical Leadership

• Partner with software engineers, platform teams, product managers, and business stakeholders to transition successful prototypes into production environments.
• Provide technical leadership throughout deployment and operationalization activities.
• Drive architectural decisions for AI solutions while balancing innovation, scalability, security, compliance, and operational requirements.
• Mentor engineers and data scientists and provide guidance on advanced AI techniques and best practices.
• Take ownership of outcomes and ensure successful delivery of AI capabilities from concept through adoption.

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