Job Description Summary

The Sr. Director, Product Cybersecurity AI, Emerging Technology & Platforms Leader is a senior director reporting directly to the VP of Product Cybersecurity and working in close partnership with the CISO office, the GE Vernova Advanced Research Center, product and engineering professionals within the business units. This leader owns the full strategic arc of our agentic product security transformation — from securing the first line of code to responding to vulnerabilities in fielded product versions running in power plants, substations, and grid infrastructure around the world. This is a defining role at the intersection of product cybersecurity and critical infrastructure — spanning emerging technologies including agentic AI platforms, field robotics, and quantum-resilient security architectures. You will work with cross-functional teams to design and build the agentic technology strategy, the agentic pipeline of personas to support the business units in their quest to create products that are secure by design and support faster vulnerability triangulation and remediation of vulnerabilities. Build Track Agentic security capabilities embedded across every SDLC phase — threat modeling agents on design documents, real-time code review on every commit, autonomous dependency and SCA agents in the build Field Track AI-assisted vulnerability response for products already deployed in the field. CVE-to-product version mapping agents, agentic CVSS scoring across the install base, AI assisted patch and customer advisory generation

Job Description

Key Responsibilities

Program Strategy & Leadership

• Transformation Roadmap: Own the end-to-end "agentic" product security roadmap, defining clear milestones for transitioning from traditional to autonomous security operations.
• Executive Reporting: Present quarterly AI transformation scorecards to the VP of Product Cybersecurity and senior leadership.
• Cross-Functional Alignment: Partner with the CISO and Advanced Research Center to align strategies with enterprise risk frameworks and explore frontier technologies (e.g., field robotics, quantum-resilient crypto).
• Business Engagement: Embed security capabilities into business unit engineering workflows through proactive stakeholder collaboration.

Agentic Technology & Platforms

• Tooling Strategy: Lead the evaluation and selection of LLM providers, agentic tooling, and AI security platforms.
• Economic Discipline: Manage unit economics, including token cost management and per-application budgeting.
• Validation: Enforce rigorous "shadow mode" validation—requiring 95%+ parity before retiring any legacy security tools.

Build & Field Track Operations

• Secure Development (Build): Integrate security agents into CI/CD pipelines to achieve 100% repository coverage for code review and threat modeling by FY2027.
• Fielded Response (Field): Build autonomous vulnerability response capabilities; map all supported product versions to CVE exposure agents by FY2027 and reduce PSIRT advisory SLAs.

Contractor & Pipeline Governance

• Pipeline Personas: Define and govern role-based identities, permissions, and behavioral profiles for all autonomous agents.
• Program Management: Manage multi-vendor contractor programs (development, model drift monitoring, regression testing) and ensure GE Vernova ownership of all agent code/IP.
• Internal Capability: Build a resilient AI security team through strategic hiring, reskilling, and a dual-vendor strategy to mitigate single-vendor dependency.

Qualifications

Required

• Bachelors in CS, Cybersecurity, Engineering or in a related field (master’s preferred).
• 10+ years in product cybersecurity, software security, or technical leadership.
• Demonstrated experience deploying AI/ML systems within DevSecOps or software engineering contexts.
• Working knowledge of GE Vernova products (grid, power, industrial) and their operational environments.
• Deep expertise in secure SDLC, DevSecOps toolchains, and large-scale vulnerability management.
• Experience managing complex multi-vendor programs, including IP governance and performance metrics.

Desired Characteristics

• AI Fluency: Deep understanding of agentic frameworks, LLM prompt engineering, and autonomous workflow architecture.
• Emerging Tech: Awareness of frontier risks like field robotics s