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Vectra

AI-driven network detection and response platform

Director of AI

Engineering LeadershipConfirmed live in the last 24 hours
Full-timeSan Jose, CA, USAIn-person

About the Job

Requirements

  • At least 8 years of experience building, scaling, and deploying AI and machine learning systems in production environments in Engineering or IT organizations.
  • At least 3 years in a leadership role managing engineers, data practitioners, or AI and machine learning teams.
  • A proven track record shaping AI strategy that influences product and business outcomes.
  • A strong foundation in machine learning, data architecture, distributed systems, and AI tooling.
  • Hands-on experience with modern AI tools, large language models, cloud platforms, and data infrastructure.
  • A track record of deploying solutions at scale with attention to reliability, performance, and monitoring.
  • An advanced degree in Computer Science, AI/Machine Learning, IT development/Data Science, or a related field is preferred.

Responsibilities

  • Define, evolve, and execute the company’s AI strategy in alignment with business goals.
  • Evangelize the 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 generative 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 to deliver transformational programs.
  • Mentor and develop technical talent and foster a culture of collaboration, innovation, and continuous learning.
  • Set performance targets and build career paths for team members.
  • Work with Engineering, Product, Data Science, Security Research, and Go-to-Market functions to embed AI across the platform and solutions.
  • Partner with executive leaders to conduct build-versus-buy assessments, prioritize programs, conduct feasibility assessments, document requirements, and perform technical program assessments.
  • Guide architectural decisions for scalable AI and machine learning systems, data pipelines, model governance, and deployment frameworks.
  • Drive best practices for experiment tracking, monitoring, retraining, and model lifecycle management.
  • Monitor 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, particularly given the sensitive nature of customer and internal 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, including operational efficiency, return on investment/cost impact, and business value delivered.
  • Report progress, blockers, and outcomes to senior leadership.

About the Company

Vectra

AI-driven network detection and response platform

Vectra.ai builds AI-powered security tools that watch traffic in cloud environments, SaaS apps, data centers, and enterprise networks to find cyber threats in real time. Its main product, the Cognito platform, connects with other security tools like EDRs, SIEMs, firewalls, and hybrid cloud setups. It collects network data and adds machine-learned security insights, then automatically detects attacker behaviors and flags the most at-risk devices. This helps security teams investigate incidents more efficiently and hunt for threats with AI assistance. Vectra.ai differentiates itself through strong integration across many security tools and its ability to provide real-time detection and risk prioritization across a wide set of environments. The company's goal is to help large organizations reduce security risk and improve their overall security posture by quickly detecting and responding to threats across their entire cloud footprint.

Company size
501-1,000
Company stage
Series F
Total funding
$352.3M
Headquarters
San Jose, CA
Founded
2011

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