Director of AI

We’re looking for a strategic and inspired Director of AI to lead our AI and data engineering teams, drive our AI strategy, and serve as a resident expert within the organization You will shape the vision and execution of AI and machine learning initiatives across our platform, champion best-in-class architecture and engineering practices, and partner broadly with product, engineering, and business leadership to unlock the next wave of AI-driven capabilities in cybersecurity This individual will focus on creating and operationalizing AI strategy while scaling team capabilities and ensuring high ROI from AI investments Define, evolve, and execute Vectra’s AI strategy in alignment with business and product goals Evangelize AI vision and strategy to executives, cross-functional partners, and external stakeholders Translate long-term AI goals into actionable roadmaps with clear priorities and measurable outcomes Lead a team of cross-functional executives responsible for driving Gen AI initiatives in their organizations through a ‘hub-and-spoke model.’ Lead and grow high-performing teams of AI engineers, machine learning engineers, and data engineers Mentor and develop technical talent; foster a culture of collaboration, innovation, and continuous learning Set performance targets and build career paths for team members Work closely with Engineering, Product, Data Science, Security Research, and Go-to-Market functions to embed AI across Vectra’s platform and solutions Partner with executive leaders to conduct “build vs buy” assessments, prioritize programs, conduct feasibility assessments, document requirements and deliver technical programs assessments, Technical Excellence Guide architectural decisions for scalable AI/ML systems, MLOps, data pipelines, model governance, and deployment frameworks Drive best practices for experiment tracking, monitoring, retraining, and model lifecycle management Stay abreast of AI advancements — especially in machine learning, deep learning, generative models, and large-scale distributed systems — and determine how to bring relevant innovation into production Ensure responsible, secure, and ethical use of AI — especially given the sensitive nature of cybersecurity data Establish governance frameworks for model quality, bias mitigation, and compliance with internal and external standards Define and track key performance indicators for AI initiatives (e.g., model accuracy, operational efficiency, cost impact, and business value delivered) Report on progress, blockers, and outcomes to senior leadership BenefitsUnlimited PTO Healthcare Packages Global Wellness Days Employee Assistance Programs Parental Leave Fertility Assistance