Lead Information Security Engineer

Wells Fargo•Minneapolis, MN

4d•$119,000 - $206,000•Hybrid

About The Position

Wells Fargo is seeking a Lead Information Security Engineer who will support the Vulnerability Assessment Team in their scanning operations supporting multiple tools to increase efficiency and accuracy. The person filling this position will be responsible for analyzing existing technical tasks performed by engineers and building processes including our move to AI to automate tasks. This will require identifying areas where efficiencies can be gained, understanding the existing process and implementing automation of tasks. To accomplish these goals, the candidate must possess advanced security/engineering/networking skills. In this role, you will: Lead efforts to run vulnerability scans of IoT devices and work with the larger team to identify vulnerabilities on infrastructure assets. Work with team members to design, create and implement automation preferably with AI to support operational tasks Provide security consulting on large scale projects to ensure conformity with corporate information, security policy, and standards Design, document, test, maintain, and provide issue resolution recommendations for moderately complex security solutions related to networking, cryptography, cloud, authentication and directory services, email, Internet, applications, and endpoint security Utilize subject matter knowledge in industry leading security solutions and best practices to implement one or more components of information security such as availability, integrity, confidentiality, risk management, threat identification, modeling, monitoring, incident response, access management, and business continuity Identify security vulnerabilities and issues, perform risk assessments, and evaluate remediation alternatives Collaborate and consult with peers, colleagues and managers to resolve issues and achieve goals

Requirements

5+ years of Information Security Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
Advanced security/engineering/networking skills

Nice To Haves

3+ years of experience in vulnerability management and/or patch management tools and techniques.
Knowledge and understanding of Common Vulnerability Exposures (CVE) and Common Vulnerability Scoring System (CVSS) scoring
Demonstrated knowledge/experience with Qualys or like vulnerability management tool
Strong leadership, strategic thinking, and problem-solving skills

Responsibilities

Lead efforts to run vulnerability scans of IoT devices and work with the larger team to identify vulnerabilities on infrastructure assets.
Work with team members to design, create and implement automation preferably with AI to support operational tasks
Provide security consulting on large scale projects to ensure conformity with corporate information, security policy, and standards
Design, document, test, maintain, and provide issue resolution recommendations for moderately complex security solutions related to networking, cryptography, cloud, authentication and directory services, email, Internet, applications, and endpoint security
Utilize subject matter knowledge in industry leading security solutions and best practices to implement one or more components of information security such as availability, integrity, confidentiality, risk management, threat identification, modeling, monitoring, incident response, access management, and business continuity
Identify security vulnerabilities and issues, perform risk assessments, and evaluate remediation alternatives
Collaborate and consult with peers, colleagues and managers to resolve issues and achieve goals
Demonstrate proficiency in using AI‑assisted development and analysis tools (e.g., GitHub Copilot and approved code‑centric agents)
Leverage AI to accelerate system design, coding, testing, analysis, and troubleshooting
Apply strong technical judgment when validating and integrating AI‑assisted outputs into solutions
Understand and account for model limitations, security risks, and operational considerations
Apply AI responsibly in development and production environments
Ensure AI usage aligns with security, compliance, privacy, and ethical standards