Lead Artificial Intelligence Engineer (Development & Infrastructure)

US Bank

Confirmed live yesterday High trust
Closes tomorrow

Quick summary

Work type
On-site
Location
Hopkins, MNChicago, IL
Salary
$133,365–$156,900 / yr
Posted
9 days ago
Freshness
Confirmed live yesterday
Closes
Sep 25, 2026 (soon)

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $199k
This role $145k
$120k most similar roles pay here $254k

This role pays less than 88% of similar roles. Most pay $161,825–$237,065 — the shaded band above. At the midpoint, this role pays about $145k versus about $199k for comparable roles.

Based on 240 similar postings.

Employer

About US Bank

U.S. Bank (U.S. Bancorp) is the fifth-largest bank in the United States, providing retail banking, corporate and commercial banking, wealth management, and payment services to millions of customers. Industry: Banking & Financial Services

US Bank currently has 44 open roles on FindRole.

Listed pay typically runs $111,605–$131,300 across 38 roles with salary data.

Most-posted roles

View all roles at US Bank

At a glance

TL;DR · Lead Artificial Intelligence Engineer (Development & Infrastructure)

Lead Artificial Intelligence Engineer (Development & Infrastructure) joins the engineering team to design, develop, test, and maintain high-quality software experiences and AI-enabled products. The role focuses on building production-ready code for AI workflows, integrating Generative AI solutions like Retrieval-Augmented Generation pipelines using vector databases, and developing agentic AI systems capable of planning and reasoning under defined guardrails. Key responsibilities include performing root-cause analysis for model quality issues, participating in code reviews, and implementing software reliability engineering practices. The candidate will utilize Python, Java, Docker, Kubernetes, Bedrock, and LLMs while working with vector databases like Pinecone or Weaviate and frameworks such as LangChain and LangGraph. This role addresses the technical challenge of integrating advanced AI capabilities into regulated environments, ensuring scalable, secure, and performant solutions that enhance user workflows and decision-making processes within a complex financial services context.

What you'll do

  • Develop production-ready, testable code for assigned software components, services, and AI workflows.
  • Build and integrate Generative AI solutions including Retrieval-Augmented Generation (RAG) pipelines and vector databases.
  • Support the development of agentic AI systems that can plan, reason, and invoke tools under defined guardrails.
  • Troubleshoot and perform root-cause analysis for both traditional software and AI components to propose fixes.
  • Participate in code reviews to ensure implementations meet engineering, security, and compliance standards.
  • Implement scalable, reliable, and cost-effective solutions following established architectural patterns and best practices.
  • Apply software reliability engineering (SRE) practices and AI evaluation techniques to maintain product quality.
  • Propose prototypes and proofs of concept for emerging technologies in GenAI and agentic frameworks.

What we're looking for

  • Bachelor’s degree in computer science, Engineering, or related field, or equivalent practical experience.
  • Six to eight years of relevant software engineering experience.
  • 10+ years of overall software development experience in Python and Java or other object-oriented languages.
  • 3+ years of leading software projects with enterprise level solutions.
  • 2-3 years of experience with containerization and orchestration, including Docker, Kubernetes, Bedrock, LLMs, and vector databases.
  • 2-3 years of hands-on experience with Generative AI use cases, including RAG architectures, prompt engineering, and evaluation approaches.
  • Practical experience building AI applications using LangChain and LangGraph to design and orchestrate complex agent workflows.
  • 2-3 years of experience building data-driven APIs and services using Python.
  • Exposure to Knowledge Graph concepts and graph databases (preferred).
  • Familiarity with modern UI frameworks like React and how AI services integrate into user-facing applications (preferred).

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