Lead AI Engineer, Observability

US Bank

Confirmed live yesterday High trust

Quick summary

Work type
On-site
Location
Chicago, ILMinneapolis, MNCupertino, CACharlotte, NCCincinnati, OH
Salary
$139,230–$163,800 / yr
Posted
9 days ago
Freshness
Confirmed live yesterday

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $211k
This role $152k
$126k most similar roles pay here $260k

This role pays less than 86% of similar roles. Most pay $175,000–$246,150 — the shaded band above. At the midpoint, this role pays about $152k versus about $211k 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 30 open roles on FindRole.

Listed pay typically runs $119,765–$140,900 across 29 roles with salary data.

Most-posted roles

View all roles at US Bank

At a glance

TL;DR · Lead AI Engineer, Observability

Lead AI Engineer - Observability is a senior technical role focused on designing, developing, and operationalizing enterprise-scale Generative AI solutions. The engineer will build intelligent systems using Large Language Models, Retrieval-Augmented Generation architectures, prompt engineering, and agentic AI workflows. Day-to-day responsibilities include managing the full GenAIOps lifecycle, including integration with enterprise systems, monitoring, and establishing evaluation mechanisms for production environments. The role requires expertise in Python, microservices, and distributed systems across Azure and AWS cloud platforms. Key technologies include LangChain, LangGraph, AWS Bedrock, Microsoft Foundry Agent Service, Docker, Kubernetes, and Infrastructure as Code tools like Terraform or ARM/Bicep. This position addresses the challenge of delivering secure, scalable, and resilient AI capabilities within a highly regulated environment while providing architectural leadership and mentoring to engineering teams to ensure high-performance, low-latency outcomes.

What you'll do

  • Design and deploy enterprise-scale Generative AI solutions using LLMs, RAG architectures, and agentic workflows.
  • Build intelligent systems using frameworks like LangChain, LangGraph, AWS Bedrock, and Microsoft Foundry.
  • Manage the full GenAIOps lifecycle including monitoring, observability, and cost-efficient deployment.
  • Architect distributed systems on AWS and Azure using Docker, Kubernetes, and Infrastructure as Code.
  • Develop scalable microservices in Python while maintaining high security and performance standards.
  • Build and manage CI/CD pipelines for automated testing and production release management.
  • Provide technical leadership by mentoring engineers and making critical architectural design decisions.
  • Translate complex business requirements into secure, resilient technical solutions for regulated environments.

What we're looking for

  • Bachelor’s degree or equivalent work experience in Computer Science, Engineering, or a related field.
  • At least 8 years of experience in software engineering, platform engineering, or AI/ML solutions.
  • At least 2 years of hands-on experience with GenAI technologies, including LLMs and RAG architectures.
  • Proficiency in Python and microservices-based development for building scalable applications.
  • Experience with cloud platforms (Azure and/or AWS) and infrastructure tools like Docker, Kubernetes, and Terraform or Bicep.
  • Strong knowledge of agentic AI concepts and frameworks such as LangChain and LangGraph.
  • Demonstrated experience in technical leadership, mentoring, and coaching engineering teams.
  • Experience implementing GenAI solutions within regulated environments or the financial services industry.

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