Information Security Engineering Senior Manager - Cyber Defense Data & AI

Wells Fargo & Company•Iselin, NJ

About The Position

About this role: Wells Fargo is seeking an Information Security Engineering Manager in Technology as part of Cybersecurity. Learn more about the career areas and lines of business at wellsfargojobs.com The Cybersecurity Defense Management (CDM) Data and AI Manager leads the strategy and execution of data, analytics, and AI capabilities that strengthen the organization’s cybersecurity defense posture. This role oversees secure data pipelines, develops AI/ML models for threat detection and automation, and manages a comprehensive metrics program supporting operational visibility and executive decision making. The manager ensures that CDM operations are driven by accurate data, meaningful insights, and responsible use of advanced technologies. In this role, you will: Manage a team, through less experienced managers, of Information Security Engineers that design, document, test, maintain and provide issue resolution recommendations for highly complex security solutions related to networking, cryptography, cloud, authentication or directory services, email, internet, applications, or endpoint security Engage more experienced information security and line of business management to identify, formulate and implement information security solutions and controls Lead a large, complex information security unit or a number of smaller specialized work units with direct impact to companywide information security objectives having high risk and complexity Manage security consulting on large projects for internal clients to ensure conformity with corporate information security policy and standards Set guidelines for compliance and risk management requirements for supported area and work with other stakeholders to implement key risk initiatives Oversee resource allocations to ensure commitments align with strategic objectives Manage implementation of information security such as availability, integrity, confidentiality, risk management, threat identification, modeling, monitoring, incident response, access management and business continuity Maintain a broad awareness of the state of information security across the enterprise and industry Influence change to information security policy, standards and procedures for systems, applications or tools Lead large, companywide projects and initiatives Represent the organization to regulators, industry groups and governmental agencies Interface with Information Security Industry Leaders, Financial industry Leaders, Analysts and Regulators Advise more experienced leadership or executive management on issues with high, critical impact on the company Manage allocation of people and financial resources for Information Security Architecture Develop and guide a culture of talent development to meet business objectives and strategy Key Responsibilities: Leadership & Program Management Lead the CDM Data & AI function, setting strategy, priorities, and technical direction. Maintain the CDM Data & AI roadmap and align it with cybersecurity and enterprise goals. Coordinate cross‑functional initiatives with cybersecurity, IT, cloud, data, and governance teams. Oversee platforms, tools, and vendor engagements supporting analytics and AI. Data Engineering & Architecture Manage secure, scalable data pipelines for ingesting and correlating cybersecurity telemetry. Ensure data quality, governance, and consistency across CDM systems and sources. Develop and maintain security‑focused data models and standardized schemas. Partner with enterprise data teams on architecture, integration, and modernization efforts. AI & Machine Learning for Security Develop and deploy ML/AI capabilities for threat detection, anomaly detection, predictive analytics, and automation. Implement generative‑AI solutions to support triage, analysis, and reporting while maintaining security and privacy controls. Oversee MLOps processes including model training, validation, deployment, and performance monitoring. Integrate AI capabilities into SIEM, SOAR, IAM, EDR, and cloud‑security ecosystems. Metrics, Reporting & Performance Management Lead the CDM metrics program, defining KPIs/KRIs that measure control effectiveness, cyber hygiene, operational performance, and risk reduction. Produce dashboards and reports for senior leadership and governance bodies. Ensure metrics align with cybersecurity frameworks (e.g., NIST CSF, NIST 800‑53, Zero Trust). Maintain consistent, accurate, and transparent reporting across CDM environments. Security, Compliance & Risk Management Ensure secure and compliant data‑handling and AI‑development practices. Support audits, risk assessments, and compliance activities with validated data and metrics. Establish governance guidelines for responsible and ethical AI in cybersecurity operations. Collaboration & Communication Act as a liaison across cybersecurity, IT, data, audit, and compliance teams. Translate complex data and technical findings into actionable insights for non‑technical stakeholders. Mentor and guide staff on data analytics, engineering, and AI best practices.

Requirements

6+ years of Information Security Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
3+ years of management or leadership experience
Proficiency with ML frameworks (e.g., TensorFlow, PyTorch) and data engineering tools (Python, SQL, Spark).
Experience with Azure, AWS, or GCP, and security automation platforms.
Familiarity with NIST CSF, NIST 800‑53, MITRE ATT&CK, and Zero Trust.

Nice To Haves

CISSP, CISM, CCSP, GIAC, or AI/ML/cloud certifications.
Experience building generative‑AI capabilities for cybersecurity use cases.
Experience with MLOps pipelines and model lifecycle management.

Responsibilities

Lead the CDM Data & AI function, setting strategy, priorities, and technical direction.
Maintain the CDM Data & AI roadmap and align it with cybersecurity and enterprise goals.
Coordinate cross‑functional initiatives with cybersecurity, IT, cloud, data, and governance teams.
Oversee platforms, tools, and vendor engagements supporting analytics and AI.
Manage secure, scalable data pipelines for ingesting and correlating cybersecurity telemetry.
Ensure data quality, governance, and consistency across CDM systems and sources.
Develop and maintain security‑focused data models and standardized schemas.
Partner with enterprise data teams on architecture, integration, and modernization efforts.
Develop and deploy ML/AI capabilities for threat detection, anomaly detection, predictive analytics, and automation.
Implement generative‑AI solutions to support triage, analysis, and reporting while maintaining security and privacy controls.
Oversee MLOps processes including model training, validation, deployment, and performance monitoring.
Integrate AI capabilities into SIEM, SOAR, IAM, EDR, and cloud‑security ecosystems.
Lead the CDM metrics program, defining KPIs/KRIs that measure control effectiveness, cyber hygiene, operational performance, and risk reduction.
Produce dashboards and reports for senior leadership and governance bodies.
Ensure metrics align with cybersecurity frameworks (e.g., NIST CSF, NIST 800‑53, Zero Trust).
Maintain consistent, accurate, and transparent reporting across CDM environments.
Ensure secure and compliant data‑handling and AI‑development practices.
Support audits, risk assessments, and compliance activities with validated data and metrics.
Establish governance guidelines for responsible and ethical AI in cybersecurity operations.
Act as a liaison across cybersecurity, IT, data, audit, and compliance teams.
Translate complex data and technical findings into actionable insights for non‑technical stakeholders.
Mentor and guide staff on data analytics, engineering, and AI best practices.