Lead Infosecurity Engineer, AI Security Platform

US Bank

Confirmed live yesterday High trust
Hybrid

Quick summary

Work type
Hybrid
Location
Minneapolis, MNAtlanta, GACincinnati, OHCharlotte, NCBrookfield, WIChicago, ILGresham, OREnglewood, COIrving, TXEarth City, MO
Salary
$133,365–$156,900 / yr
Employment
Full-time
Posted
2 days ago
Freshness
Confirmed live yesterday
Closes
Nov 15, 2026

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $187k
This role $145k
$122k $236k
below market most similar roles pay here above market

This role pays less than 82% of similar roles. Most pay $154,450–$219,343 — the blue band above. At the midpoint, this role pays about $145k versus about $187k 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 46 open roles on FindRole.

Listed pay typically runs $119,765–$140,900 across 28 roles with salary data.

Most-posted roles

View all roles at US Bank

At a glance

TL;DR · Lead Infosecurity Engineer, AI Security Platform

JOB TITLE: Lead Infosecurity Engineer - AI Security Platform The Lead Infosecurity Engineer - AI Security Platform leads the engineering and operational enablement of commercial agentic security operations platforms and AI-powered security capabilities. This role connects security operations, engineering, architecture, and AI engineering to deliver production-ready solutions. You will build and maintain RAG architectures, agent orchestration frameworks, evidence acquisition pipelines, and AI workflow integrations. Key responsibilities include designing scalable integrations across Microsoft Sentinel, SOAR, threat intelligence, and cloud security platforms while establishing secure engineering standards. You will utilize Python, REST APIs, Infrastructure as Code, and tools like LangChain, LangGraph, and Azure OpenAI. The work focuses on transforming security investigations through autonomous investigation capabilities, intelligent decision-support, and robust governance to mitigate risks associated with AI models, data flows, and third-party technologies in a regulated environment.

What you'll do

  • Lead the implementation and support of Agentic SOC and AI-powered security operations platforms.
  • Design and develop security automation solutions using Python, REST APIs, and Infrastructure as Code.
  • Build and maintain RAG architectures, agent orchestration frameworks, and evidence acquisition pipelines.
  • Establish secure engineering standards and architecture frameworks for AI-enabled security services.
  • Integrate AI platforms with Microsoft Sentinel, SOAR, threat intelligence, and cloud security systems.
  • Implement AI observability, monitoring, and auditability capabilities to ensure operational governance.
  • Identify security risks related to AI models and data flows while developing practical mitigation strategies.
  • Partner with internal teams to improve detection, triage consistency, and autonomous investigation capabilities.

What we're looking for

  • 7+ years of cybersecurity engineering experience across multiple information security domains.
  • 2+ years of hands-on experience implementing AI, Generative AI, Machine Learning, Agentic AI, or AI platform technologies.
  • Experience building and supporting security automation, SOAR, or enterprise security platform engineering solutions.
  • Strong software engineering skills with Python, API development/integration, and automation of security workflows.
  • Experience with Microsoft Sentinel, security orchestration technologies, and production Security Operations environments.
  • Hands-on experience with Azure, AWS, cloud-native services, and Infrastructure as Code (Terraform, Bicep, ARM, or similar).
  • Knowledge of LangChain, LangGraph, Semantic Kernel, LlamaIndex, MCP, RAG architectures, and enterprise AI services (preferred).
  • Experience with vector databases, graph technologies, or supporting highly regulated environments (preferred).

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