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U.S. Bank

Mid-Level AI Platform Engineer

U.S. Bank

Senior Engineer (Generative AI) at U.S. Bank designing and deploying scalable AI solutions.

Posted 6/17/2026full-timeChicago • California, Illinois, Minnesota, Ohio • 🇺🇸 United StatesMid-LevelSenior💰 $111,095 - $130,700 per yearWebsite

Tech Stack

Tools & technologies
AWSAzureCloudDistributed SystemsDockerKubernetesPythonTerraform

About the role

Key responsibilities & impact
  • Develop and implement GenAI applications leveraging: Large Language Models (LLMs)
  • Retrieval-Augmented Generation (RAG) architectures
  • Prompt engineering techniques
  • Agentic AI concepts and workflows
  • Build intelligent pipelines using frameworks such as LangChain, LangGraph, and Microsoft Foundry Agent Service
  • Evaluate solution performance, accuracy, and scalability of GenAI implementations
  • Contribute to the end-to-end GenAI lifecycle, including: Solution design and development
  • Integration and deployment
  • Performance tuning and optimization
  • Support secure deployment, horizontal scaling, and operational stability of GenAI workloads
  • Assist in implementing monitoring, logging, and observability practices for production environments
  • Develop and deploy GenAI systems across cloud platforms (Azure and AWS)
  • Contribute to distributed system design for scalable AI workloads
  • Utilize modern infrastructure practices: Containerization (Docker)
  • Orchestration (Kubernetes)
  • Infrastructure as Code (Terraform, ARM/Bicep)

Requirements

What you’ll need
  • Bachelor’s degree in Computer Science, Engineering, or related field
  • 5–8 years of experience in software or platform engineering
  • 2+ years hands-on experience with GenAI systems, including LLMs and RAG architectures and vector databases
  • Understanding of agentic AI concepts and exposure to frameworks such as LangChain or LangGraph
  • Experience with cloud platforms (Azure and/or AWS)
  • Knowledge of distributed systems and scalable application design
  • Proficiency in Python development
  • Experience with Docker, Kubernetes, and Infrastructure as Code tools
  • Experience deploying GenAI or ML solutions in production environments
  • Familiarity with observability and monitoring tools
  • Understanding of AI governance, compliance, and security practices
  • Experience in financial services or other regulated industries is a plus

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

ATS Keywords

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Hard Skills & Tools
Large Language Models (LLMs)Retrieval-Augmented Generation (RAG)Prompt engineeringGenAI systemsPythonContainerizationOrchestrationInfrastructure as CodePerformance tuningScalable application design
Certifications
Bachelor’s degree in Computer ScienceBachelor’s degree in Engineering