Mid-Level AI Platform Engineer

U.S. Bank

Senior Engineer responsible for designing and deploying scalable Generative AI solutions within an enterprise environment at U.S. Bank.

Posted 7/15/2026full-timeChicago • California, Illinois, Minnesota, Ohio • 🇺🇸 United StatesMid-LevelSenior💰 $111,095 - $130,700 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and implementing GenAI applications using Large Language Models and Retrieval-Augmented Generation architectures, with a strong focus on performance tuning, secure deployment, and scalable application design. Proficient in Python development and modern infrastructure practices, ensuring solutions meet enterprise standards for availability and security.

Highest-signal resume keywords

GenAI Application DevelopmentLarge Language Models (LLMs)Retrieval-Augmented Generation (RAG)Python DevelopmentCloud Platforms (Azure, AWS)

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

GenAI SystemsDistributed Systems DesignPerformance TuningSecure Coding StandardsMicroservices ArchitectureCI/CD PipelinesAutomated TestingData Handling PracticesObservability PracticesAgentic AI Concepts

Tools & Technologies

LangChainLangGraphDockerKubernetesTerraformARM/BicepMicrosoft Foundry Agent Service

Industry Keywords

Financial ServicesRegulated IndustriesAI GovernanceComplianceSecurity Practices

Tech Stack

Tools & technologies

AWSAzureCloudDistributed SystemsDockerKubernetesMicroservicesPythonTerraform

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)
Ensure solutions meet enterprise expectations for availability, performance, and security
Develop scalable applications using Python and microservices-based architectures
Apply secure coding standards and proper data handling practices for enterprise, regulated environments
Contribute to CI/CD pipelines, automated testing, and deployment workflows
Participate in code reviews and adhere to engineering best practices

Requirements

What you’ll need

Bachelor’s degree, or equivalent work experience
Three to five years of relevant experience
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