Lead Infosecurity Engineer – AI Security Platform

U.S. Bank

. Lead the implementation, integration, deployment, and support of Agentic SOC, AI-powered security operations, and autonomous investigation capabilities .

Posted 10/28/2026full-timeUnited StatesSenior💰 $133,365 - $156,900 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates extensive experience in cybersecurity engineering, focusing on AI-powered security operations, automation solutions, and risk management. Proficient in leading complex technical initiatives and establishing secure engineering standards across various security platforms.

Highest-signal resume keywords

Cybersecurity Engineering ExperienceAI Implementation ExperiencePython Development SkillsMicrosoft Sentinel ExpertiseCloud Services Proficiency

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Cybersecurity EngineeringAI ImplementationPython ProgrammingAPI DevelopmentSecurity AutomationInfrastructure as CodeCloud ServicesRisk ManagementSecurity OrchestrationData Flow Analysis

Soft Skills

LeadershipCommunicationMentoringInfluencing StakeholdersProject Management

Tools & Technologies

Microsoft SentinelAzureAWSTerraformKubernetesLangChainLangGraphSemantic KernelAzure OpenAISecurity Copilot

Industry Keywords

Financial ServicesBankingHealthcareRegulated EnvironmentsSecurity Operations

Tech Stack

Tools & technologies

AWSAzureCloudCyber SecurityKubernetesNeo4jPythonRedisTerraform

About the role

Key responsibilities & impact

Lead the implementation, integration, deployment, and support of Agentic SOC, AI-powered security operations, and autonomous investigation capabilities
Design and develop security automation solutions using Python, REST APIs, cloud services, and Infrastructure as Code
Build and maintain RAG architectures, agent orchestration frameworks, evidence acquisition pipelines, knowledge retrieval services, and AI workflow integrations
Establish secure engineering standards, reusable patterns, and architecture frameworks for AI-enabled security platforms and services
Design scalable integrations across Microsoft Sentinel, SOAR, threat intelligence, endpoint, identity, cloud, and email security platforms
Implement AI observability, monitoring, auditability, and explainability capabilities
Identify AI-related security risks across models, agents, data flows, cloud platforms, and third-party technologies and develop mitigation strategies
Partner with Security Operations, Architecture, Risk, Data, and Technology teams to improve detection, triage consistency, autonomous investigations, and reduce MTTR
Provide project and change leadership, security oversight, and risk management for complex information security initiatives
Set design guidelines and implementation patterns, identify emerging risks, and influence senior leaders toward simplified solutions
Train and mentor team members and may contribute to projects developing new intellectual property

Requirements

What you’ll need

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, AI orchestration frameworks, Azure OpenAI, or Security Copilot
Ability to lead complex technical initiatives, communicate security risk to senior stakeholders, and influence scalable, risk-aligned solutions
Preferred: experience with vector databases and retrieval services such as Azure AI Search, Pinecone, or Redis Vector
Preferred: knowledge of AI governance, observability, audit logging, data lineage, and model monitoring
Preferred: experience with graph technologies such as Neo4j, Amazon Neptune, or TigerGraph
Preferred: familiarity with Kubernetes, cloud-native architectures, and security data engineering
Preferred: experience supporting highly regulated environments such as financial services, banking, or healthcare
Ability to comply with U.S. Bank policies and procedures, including the Code of Ethics and Business Conduct and related workplace conduct and safety policies
Applicants must be able to satisfy applicable employment eligibility verification and background-check requirements

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
Incentive and recognition programs
Equity stock purchase
401(k) contribution and pension