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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in developing and deploying AI solutions, particularly in generative AI and machine learning, while effectively communicating complex concepts to stakeholders. Proven ability to lead AI architecture decisions and mentor teams in a highly regulated environment.
Highest-signal resume keywords
Python ProgrammingGenerative AI ExpertiseAI/ML Solution DeploymentMachine Learning FrameworksAI Research and Experimentation
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Machine LearningDeep LearningNeural NetworksTransformer ArchitecturesFoundation ModelsModel EvaluationInference OptimizationAgentic AI SystemsMulti-Agent WorkflowsAI Orchestration Frameworks
Soft Skills
Strong Communication SkillsMentoring
Tools & Technologies
PyTorchHugging FaceLangChainLangGraphAI/ML Frameworks
Industry Keywords
Financial ServicesHealthcareInsuranceTelecommunicationsRegulatory ComplianceFINRANMLSBank Secrecy ActSAFE Act
Tech Stack
Tools & technologiesCloudPythonPyTorch
About the role
Key responsibilities & impact- Monitor, evaluate, and experiment with emerging AI technologies, research breakthroughs, and industry trends, especially generative AI, LLMs, multimodal AI, and agentic AI systems
- Identify opportunities to apply advanced AI techniques to complex financial-services business problems
- Conduct original AI research and exploratory investigations
- Develop hypotheses, design experiments, evaluate results, and communicate findings to technical and executive stakeholders
- Contribute to publications, patents, technical whitepapers, and thought leadership initiatives
- Transform research concepts into working prototypes and proof-of-concepts
- Design, develop, and validate AI solutions from data preparation and modeling through deployment and monitoring
- Build experimental and production-ready solutions using modern AI/ML tools, frameworks, and cloud platforms
- Lead development of foundation-model, generative AI, RAG, fine-tuning, and agentic-workflow solutions
- 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 LLM governance
- Partner with engineers, platform teams, product managers, and business stakeholders to transition prototypes into production
- Drive AI architecture decisions while balancing innovation, scalability, security, compliance, and operations
- Mentor engineers and data scientists
- Own delivery of AI capabilities from concept through adoption
- Serve as technical owner for AI platforms, frameworks, and shared services
Requirements
What you’ll need- Bachelor's degree in a quantitative field such as statistics, computer science, engineering, or applied mathematics, or equivalent work experience
- Eight or more years of relevant experience
- Strong programming skills in Python and modern AI/ML frameworks
- Experience designing, building, and deploying AI/ML solutions in production environments
- Experience across the full AI product lifecycle, from research and experimentation through deployment and operationalization
- Deep expertise in machine learning, deep learning, neural networks, transformer architectures, and foundation models
- Extensive experience with generative AI, including LLMs, fine-tuning, RAG systems, model evaluation, and inference optimization
- Experience building and evaluating agentic AI systems, multi-agent workflows, AI orchestration frameworks, and autonomous decision-making architectures
- Hands-on experience with PyTorch, Hugging Face, LangChain, LangGraph, or equivalent AI ecosystems
- Demonstrated innovation through publications, patents, open-source contributions, conference presentations, or significant AI solution delivery
- Experience developing AI solutions in highly regulated industries such as financial services, healthcare, insurance, or telecommunications
- Strong communication skills and ability to translate complex AI concepts into actionable business outcomes
- Applicants must be able to comply with U.S. Bank policies and procedures, including the Code of Ethics and Business Conduct and workplace conduct and safety policies
- Position may be subject to applicable regulatory requirements, including FINRA, NMLS, Reg Z, Reg G, OFAC, NFA, FCPA, Bank Secrecy Act, SAFE Act, or federal guidelines
Benefits
Comp & perks- 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
- Comprehensive benefits package
- Incentive and recognition programs
- Equity stock purchase
- 401(k) contribution and pension
- Disability accommodations during the application or hiring process