Technology Director - Cybersecurity Engineering

Wells Fargo•Iselin, NJ

2d•$215,000 - $355,000•Hybrid

About The Position

Wells Fargo is seeking a Technology Director for Cyber Engineering to lead engineering solutions for next-generation security assessment, automated SaaS assurance, AI security validation, cyber risk intelligence, and Just-in-Time (JIT) access. The role shapes Cyber Engineering’s direction across emerging technology domains and leads strategic initiatives including the AI Security Test Harness, unified findings and thematic risk analysis, AI Security and Threat Assessment Automation, Mindgard.ai and Cisco Cyber Defense AI initiatives, and enterprise-scale JIT access management focused on endpoint security controls, privileged access governance, and secure-by-design solutions. The director develops business cases and executive technical roadmaps, evaluates build-versus-buy options, influences architectural designs, and drives cross-functional execution across cybersecurity, identity, product engineering, infrastructure, and operations. The role partners with senior technology leaders to deliver scalable security capabilities that reduce risk, strengthen governance, and improve operational efficiency while supporting enterprise modernization. It also leads, builds, and manages a team of advanced software engineers with diverse subject-matter expertise. The position provides dedicated technical leadership to evaluate emerging technologies, lead proofs of concept, and scale innovative ideas into enterprise capabilities in response to security risks associated with AI, cloud-native technologies, SaaS platforms, and automated software delivery. Through technical leadership, experimentation, and collaboration, it advances security effectiveness, automation, and operational resilience.

Requirements

10+ years of Technology Strategic Leadership experience, or equivalent demonstrated through work experience, training, military experience, or education.
4+ years of management or leadership experience.
Demonstrated proficiency using AI-assisted development and analysis tools, such as GitHub Copilot and approved code-centric agents.
Strong technical judgment when validating and integrating AI-assisted outputs into solutions.

Nice To Haves

10+ years of software engineering experience, including at least 3–5 years in a managerial or technical leadership role.
Proven experience delivering AI/ML and GenAI solutions, preferably in cybersecurity or a related high-security domain.
Strong knowledge of the machine learning lifecycle, LLMs, MLOps practices, model deployment, and monitoring.
Familiarity with enterprise cybersecurity use cases and data sources such as logs, telemetry, user behavior, and threat intelligence.
Hands-on experience with modern data and AI stacks such as Python, TensorFlow, PyTorch, Spark, Hugging Face, Vertex AI, Databricks, LangChain, and vector databases.
Experience designing scalable microservices and data pipelines in a hybrid cloud environment.
Experience evaluating and integrating third-party enterprise tools and open-source frameworks.
Strong problem-solving skills, business acumen, and ability to communicate complex technical concepts to non-technical stakeholders.
Demonstrated experience building and nurturing strong, diverse engineering teams.
Experience with Generative AI frameworks such as OpenAI, Anthropic, Mistral, and LLaMA, and with Retrieval-Augmented Generation (RAG).

Responsibilities

Lead strategic engineering initiatives, including the AI Security Test Harness, unified findings and thematic risk analysis, and AI Security and Threat Assessment Automation.
Partner with cyber engineering leaders on initiatives such as Mindgard.ai and Cisco Cyber Defense AI.
Lead enterprise-scale Just-in-Time access management solutions focused on endpoint security controls, privileged access governance, and secure-by-design solutions.
Develop business cases and executive technical roadmaps; evaluate build-versus-buy options, influence architecture, and drive cross-functional execution.
Collaborate with product managers, data scientists, platform teams, and security experts to define roadmaps and architecture.
Provide technical leadership in design reviews, code reviews, and architecture discussions.
Track industry trends in AI, ML, GenAI, and cybersecurity and introduce innovative approaches and tools.
Guide adoption and implementation of enterprise AI/ML platforms and champion custom-built solutions when appropriate.
Build, manage, and mentor a high-performing engineering team, fostering innovation, ownership, and collaboration.
Ensure engineering practices meet high standards for security, performance, and scalability.
Partner with cross-functional leaders to align engineering efforts with business objectives.
Define and track KPIs and OKRs for engineering execution, team growth, and solution impact.
Represent the product technically in cross-team collaboration and planning.
Identify and recommend opportunities to resolve technology roadblocks involving code, build, and deployment; manage the software development cycle and security standards.
Use AI-assisted tools to accelerate system design, coding, testing, analysis, and troubleshooting, while validating outputs and accounting for model limitations, security risks, and operational considerations.
Ensure AI use in development and production aligns with security, compliance, privacy, and ethical standards.