Principal Solution Architect - AI

at  US Bank National Association

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.

BASIC QUALIFICATIONS

• Bachelor’s degree, or equivalent work experience
• Eight or more years of relevant experience

PREFERRED SKILLS/EXPERIENCE

• Hands-on experience leading complex Gen AI architecture projects.
• Experience working with Azure and/or AWS, AND Large Language Models
• Experience in Enterprise Architecture and familiarity with architecture frameworks and methods.
• Knowledge of Cloud engineering, application architectures, application patterns and domain driven microservices.
• Ability to influence engineers and leadership on key engineering concepts and drive change to align with modern technology approaches.
• Strong understanding and prior experience with Proof of Concepts and blueprints.

ABOUT THE ROLE

This Principal Solution Architect will be responsible for rapid implementation of AI/Gen AI projects through Proof-of-concepts/pilots/MVPs in collaboration with AI COE and Tech teams to demonstrate that it is scalable solution. The role will oversee AI/Gen AI implementations, translate business requirements into recommended solution architecture, coordinate with risk and compliance partners, and address any integration needs. You’ll work in tandem with PTA discovery teams & business stakeholders to provide inputs on feasibility and help prioritize to drive business value. This is a critical role for PTA in executing AI initiatives rapidly and realizing intended business outcomes.

RESPONSIBILITIES

• Define and oversee the AI/ML/Gen AI technical direction and architectural vision, ensuring alignment with strategic goals and automation efforts.
• Translate the vision of business leaders into realistic technical implementations, while identifying misaligned initiatives and impractical use cases
• Key contributor in architecting a comprehensive AI Engineering framework that supports the deployment, evaluation, and management of ML models & Gen AI solutions.
• Select appropriate technologies from a pool of open-source and commercial offerings, considering deployment models and integration with existing tools.
• Understand and contribute to MLOps and LLMOps, focusing on operational capabilities and infrastructure to deploy and manage machine learning models and large language models.
• Collaborate with Enterprise, Application, Data & DevOps Architects, Data scientists, Machine Learning & Gen AI Engineers, and Business teams to pilot use cases and discuss architectural design.
• Gather inputs from multiple stakeholders to align technical implementation with existing and future requirements.
• Develop and maintain contact with top decision makers, lead proposal development, and contribute to pricing strategies.
• Be responsible for the successful execution of AI-powered applications using agile methodology.
• Audit AI tools and practices across data, models, and software engineering, focusing on continuous improvement and feedback mechanisms.
• Contribute to standardizing CI/CD pipelines, user and service roles, and container creation, model consumption, testing, and deployment methodology based on business and security requirements.
• Work closely with security and risk leaders to foresee and mitigate risks, ensuring ethical AI implementation and compliance with upcoming regulations.
• Address potential issues such as training data poisoning, AI model theft, and adversarial samples.
• Help AI product managers and business stakeholders understand the potential and limitations of AI when planning new products.
• Break down client problems and bring an understanding of leading technology, analytics methods, tools, and operating model approaches.
• Build tools and capabilities that assist with data ingestion, feature engineering, data management, and organization.
• Design, implement, and maintain distributed computing solutions for data processing and model training, ensuring the security, scalability, and reliability of machine learning infrastructure.

Our approach to benefits and total rewards considers our team members’ whole selves and what may be needed to thrive in and outside work. That’s why our benefits are designed to help you and your family boost your health, protect your financial security and give you peace of mind. Our benefits include the following (some may vary based on role, location or hours):

• Healthcare (medical, dental, vision)
• Basic term and optional term life insurance
• Short-term and long-term disability
• Pregnancy disability and parental leave
• 401(k) and employer-funded retirement plan
• Paid vacation (from two to five weeks depending on salary grade and tenure)
• Up to 11 paid holiday opportunities
• Adoption assistance
• Sick and Safe Leave accruals of one hour for every 30 worked, up to 80 hours per calendar year unless otherwise provided by la