Lead AI/ML Solutions Engineer
About The Position
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 role requires working from a U.S. Bank location three (3) or more days per week. U.S. Bank is seeking a Lead AI/ML Solutions Engineer to help accelerate the adoption of AI capabilities across the enterprise. This individual will serve as a technical bridge between business stakeholders, application development teams, and the AI platform organization, helping identify opportunities, design solutions, and guide implementation of AI-powered capabilities. This person will leverage a strong software engineering foundation and modern AI technologies to solve complex business problems. They will partner with business and technology teams to design, build, and scale AI-enabled solutions while ensuring security, reliability, maintainability, and responsible AI practices.
Requirements
- 8+ years of hands-on software engineering experience developing enterprise applications
- Strong programming experience in Java, Python, C#, Go, or similar object-oriented languages
- Experience implementing LLM, RAG, Agentic AI, or Generative AI solutions in production environments
- Experience with LangChain, LangGraph, Semantic Kernel, MCP, or similar AI frameworks
- Experience with Azure OpenAI, AWS Bedrock, Vertex AI, or comparable AI platforms
- Experience designing and implementing distributed systems and microservices architectures
- Strong understanding of software engineering fundamentals, design patterns, algorithms, data structures, and SDLC practices
- Experience building REST APIs and event-driven applications
- Experience with cloud platforms such as Azure, AWS, or GCP
- Experience with Kubernetes, Docker, CI/CD pipelines, and modern DevOps practices
- Architecture and solution design experience within enterprise environments
- Strong communication skills and ability to work effectively with both technical and non-technical stakeholders
- Experience leading technical discussions and influencing engineering decisions
- Ability to translate business requirements into scalable technical solutions
- Experience supporting solutions from design through deployment and production support
Nice To Haves
- Financial services, banking, or other highly regulated industry experience
- Experience with AI governance, observability, guardrails, and responsible AI practices
- Experience supporting enterprise AI platform adoption at scale
- Experience mentoring engineers or serving as a technical lead
- Familiarity with vector databases, retrieval architectures, and AI evaluation frameworks
- Experience with AI compliance, auditability, and risk management controls
- Experience working across multiple stakeholder groups to drive adoption of new technology solutions
- Experience with large-scale cloud modernization or platform transformation initiatives
- Experience with distributed systems operating at enterprise scale
- Experience building reusable frameworks, accelerators, or platform capabilities used across multiple teams
Responsibilities
- Partner with business stakeholders to identify and evaluate AI/ML opportunities
- Translate business requirements into scalable technical solutions
- Design and guide implementation of AI-enabled applications, services, and workflows
- Provide technical leadership across architecture, APIs, microservices, and cloud-native solutions
- Help development teams implement solutions using LLMs, RAG, agent frameworks, and modern AI capabilities
- Collaborate with platform engineering teams to leverage approved enterprise AI technologies and standards
- Participate in architecture reviews, design discussions, and technical decision-making
- Troubleshoot technical challenges and remove blockers impacting solution delivery
- Promote software engineering best practices, DevOps principles, and responsible AI implementation
- Mentor engineers and contribute to reusable patterns, standards, and technical documentation
- Work directly with business and technology partners to drive adoption of AI solutions across the enterprise
- Evaluate technical tradeoffs and recommend appropriate architectural approaches
Benefits
- 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 law
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
