Mid-Level AI Platform Engineers

U.S. Bank National Association • Chicago, IL

1d • $111,095 - $130,700 • Hybrid

About The Position

The Senior Engineer (Generative AI) is responsible for designing, developing, and deploying scalable Generative AI (GenAI) solutions within an enterprise environment. This role requires strong hands-on expertise in LLM-based applications, GenAI architectures, and modern cloud-native engineering practices. The position partners closely with cross-functional teams to build production-ready AI systems that meet enterprise standards for scalability, security, and reliability.

Requirements

• 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

Nice To Haves

• Experience in financial services or other regulated industries is a plus

Responsibilities

• Develop and implement GenAI applications leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) architectures, Prompt engineering techniques, and 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, and 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 including Containerization (Docker), Orchestration (Kubernetes), and 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.

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

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level