Director of AI Engineering – Generative AI & Autonomous Systems (10033) Toronto, Canada

<strong>Introduction</strong>&nbsp;

At our Extreme, we create effortless networking experiences that empower people and organizations to advance. We are seeking a <strong>Director of AI Engineering</strong> to lead the design, development, and delivery of our next-generation AI-native systems.&nbsp;

This role requires a <strong>proven leader who combines technical depth with organizational vision</strong>. You will not only set the direction for AI strategy but also ensure that ideas move from research to scalable, production-ready deployments. Your leadership will drive the successful launch of enterprise-grade AI solutions that transform network design, optimization, security, and support.&nbsp;

Key Responsibilities

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<strong>Leadership &amp; Vision&nbsp;</strong>

<li>Define the AI engineering vision and long-term roadmap; ensure alignment with business strategy and customer outcomes.&nbsp;</li>

<li>Build, inspire, and scale a world-class AI engineering team, cultivating a culture of innovation, collaboration, and execution.&nbsp;</li>

<li>Mentor senior engineers and emerging leaders, raising the technical and leadership bar across the organization.&nbsp;</li>

<li>Champion responsible AI practices and set quality standards for reliability, ethics, and compliance.&nbsp;</li>

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<strong>End-to-End Productization&nbsp;</strong>

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<li>Drive the full lifecycle of AI systems: from research exploration and prototyping through enterprise-scale production launches.&nbsp;</li>

<li>Ensure seamless integration of AI into core products, balancing cutting-edge innovation with pragmatic delivery.&nbsp;</li>

<li>Establish and enforce best practices for deployment, monitoring, and lifecycle management of AI systems in production.&nbsp;</li>

<li>Measure impact and ensure that AI solutions deliver tangible business value.&nbsp;</li>

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<strong>Technical Leadership&nbsp;</strong>

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<li>Provide architectural direction for scalable AI systems leveraging LLMs, multi-agent systems, and generative models.&nbsp;</li>

<li>Guide technical decisions, ensuring systems are reliable, secure, and cloud-native.&nbsp;</li>

<li>Evaluate emerging technologies and frameworks; make informed adoption decisions that strengthen competitive differentiation.&nbsp;</li>

<li>Maintain enough hands-on involvement to earn respect from engineers, while staying focused on strategic leadership.&nbsp;</li>

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<strong>Cross-Functional &amp; External Influence&nbsp;</strong>

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<li>Partner with product management, engineering, and network experts to define and deliver AI-driven features.&nbsp;</li>

<li>Communicate strategy, progress, and impact to executives, customers, and partners with clarity and influence.&nbsp;</li>

<li>Represent the company externally as a thought leader in AI, contributing to industry forums, open-source communities, and customer engagements.&nbsp;</li>

Qualifications

<li>A degree in Computer Science, Artificial Intelligence, or a related field (or equivalent practical experience).&nbsp;</li>

<li>Proven leadership track record: 12+ years in AI/ML engineering, including 5+ years in senior leadership roles managing teams and large-scale initiatives.&nbsp;</li>

<li>End-to-end product launch expertise: Demonstrated success leading AI initiatives from concept through production deployment and adoption at enterprise scale.&nbsp;</li>

<li>Strategic leadership: Ability to define AI roadmaps, prioritize investments, and align execution with business outcomes.&nbsp;</li>

<li>Team builder &amp; mentor: Experience scaling teams, developing leaders, and creating a culture of technical excellence.&nbsp;</li>

<li>Technical credibility: Strong foundation in ML/AI with applied expertise in generative AI, LLMs, RAG, or multi-agent systems; able to guide architecture and evaluate tradeoffs.&nbsp;</li>

<li>Enterprise-scale delivery: Experience integrating AI into production systems with cloud-native architectures (AWS, Azure, GCP).&nbsp;</li>

<li>Influence &amp; communication: Exceptional ability to engage executives, engineers, and customers with clarity and impact.&nbsp;</li>

Nice to Have:

<li>Experience with AI/LLMOps platforms, orchestration frameworks, and lifecycle management.&nbsp;</li>

<li>Domain knowledge in networking, SD-WAN, or observability.&nbsp;</li>

<li>Recognized contributions to the AI ecosystem (open-source projects, patents, or industry thought leadership).&nbsp;</li>

<li>Partnerships with academia, startups, or AI vendors to accelerate innovation.&nbsp;</li>