Software Engineer 2 (Backend AI)
U.S. Bancorp
- Location
- Earth City, MO
- Work model
- On-Site
- Level
- Mid
- Posted
- 1d ago
Skills
About this role
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.
Job Description
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 DevOps principles. Essential Responsibilities: - Responsible for designing, developing, testing, operating and maintaining products - Takes full stack ownership by consistently writing production-ready and testable code - Consistently creates optimal design adhering to architectural best practices; considers scalability, reliability and performance of systems/contexts affected when defining technical designs - Performs analysis on failures, propose design changes, and encourage operational improvements - Makes sound design/coding decisions keeping customer experience in the forefront - Takes feedback from code review and apply changes to meet standards - Conducts code reviews to provide guidance on engineering best practices and compliance with development procedures - Accountable for ensuring all aspects of product development follow compliance and security best practices - Exhibits relentless focus in software reliability engineering standards embedded into development standards - Embraces emerging technology opportunities and contributes to the best practices in support of the bank’s technology transformation - Contributes to a culture of innovation, collaboration and continuous improvement - Reviews tasks critically and ensures they are appropriately prioritized and sized for incremental delivery; anticipates and communicates blockers and delays before they require escalation Basic Qualifications - Bachelor’s degree, or equivalent work experience - Three to five years of relevant experience *This role is not eligible for visa sponsorship or transfer of visa sponsorship* Preferred Qualifications Developed and deployed AI/GenAI-powered applications utilizing Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), embedding models, and prompt engineering techniques. Designed and implemented intelligent AI workflows using agentic frameworks including LangChain, LangGraph, Semantic Kernel, and related orchestration technologies. Integrated Azure OpenAI, Azure AI Services, AWS Bedrock, and other LLM platforms into enterprise-scale applications and business processes. Built and consumed REST APIs, GraphQL services, and microservices architectures using Java, Python, Spring Boot, FastAPI, and Node.js. Integrated AI capabilities with enterprise systems, data platforms, APIs, business workflows, and cloud-native architectures. Leveraged vector databases, SQL Server, PostgreSQL, MongoDB, and related data technologies to support AI-driven solutions and scalable applications. Implemented containerization and orchestration solutions using Docker, Kubernetes, CI/CD pipelines, GitHub, and DevOps tooling. Applied expertise in distributed systems, scalability, observability, performance tuning, and high-availability cloud environments across Azure and AWS. Utilized GitHub Copilot and other AI-assisted development tools to accelerate software delivery, code quality, and engineering productivity.