Senior AI​/ML Software Engineer

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.

This position will be responsible for the analysis, design, testing, development and maintenance of best in class software experiences. The candidate is a self-motivated individual who can collaborate with a team and across the organization. The candidate takes responsibility of the software artifacts produced adhering to U.S. Bank standards in order to ensure minimal impact to the customer experience. The candidate will be adept with the agile software development lifecycle and Dev Ops principles.

Design, develop, train, fine-tune, deploy, and maintain Machine Learning models, Generative AI solutions, and Large Language Models (LLMs) to support enterprise business use cases.

Build and optimize Retrieval-Augmented Generation (RAG) architectures using vector databases, semantic search, Azure AI Search, and enterprise knowledge repositories.

Develop and manage Agentic AI systems utilizing workflow orchestration, tool invocation, multi‑agent collaboration, guardrails, and frameworks such as Lang Chain and Lang Graph.

Establish and execute AI model lifecycle management practices including model training, evaluation, validation, monitoring, retraining, versioning, and performance optimization.

Design and implement cloud‑native AI platforms and services using Python, Java, Docker, Kubernetes, and Azure AI services to support scalable and resilient production workloads.

Build and maintain AI-powered APIs, microservices, integrations, and data pipelines that enable seamless consumption of AI capabilities across applications and business processes.

Ensure compliance with Responsible AI, Model Risk Management, security, privacy, governance, and regulatory requirements while operating within a highly regulated financial services environment.

Partner with product, engineering, data science, business, and governance teams to define AI solutions, communicate technical decisions, and drive innovation through prototypes and production‑ready architectures.

Strong software engineering expertise in Python, Java, and object‑oriented application development, with the ability to design, build, test, deploy, and maintain scalable software solutions.

Hands‑on experience building Generative AI solutions, Machine Learning Models, including Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), prompt engineering, AI evaluation techniques, Model Risk Management, and production‑grade AI applications.

Experience developing Agentic AI systems leveraging multi‑step reasoning, workflow orchestration, tool invocation, guardrails, and modern frameworks such as Lang Chain and Lang Graph.

Proficiency with Vector Databases and semantic search technologies including Azure AI Search, enabling AI‑powered retrieval and knowledge solutions.

Experience designing and implementing cloud‑native, containerized applications using Docker, Kubernetes, and modern cloud platforms and AI services.

Strong understanding of software architecture, algorithms, data structures, design patterns, scalability, reliability, performance optimization, and software reliability engineering (SRE) practices.

Knowledge of responsible AI, data privacy, security, compliance, and governance principles, with the ability to implement AI solutions in regulated environments.

Experience building data‑driven APIs, services, and integrations, with exposure to Knowledge Graphs, graph databases, and modern user interfaces such as React.

Proven ability to collaborate effectively across…