Director of AI Engineering – Generative AI & Autonomous Systems (10033)
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Before you apply
LocationToronto, Canada
Work modehybrid
Typefull-time
SeniorityDirector
Experience12+ yrs
DepartmentProducts, Engineering
Company size1,001–5,000 people
PostedSep 24, 2025 · 1y ago
Verified live3d ago
May no longer be actively hiring
Posted by the company on Sep 24, 202551% of this company's open roles have been listed for 90+ days
At a glanceSummarised by Seekless from the posting.
A degree in Computer Science, Artificial Intelligence, or a related field (or equivalent practical experience)
12+ years in AI/ML engineering, including 5+ years in senior leadership roles
End-to-end product launch expertise: success leading AI initiatives from concept through production deployment at enterprise scale
Strategic leadership: Ability to define AI roadmaps, prioritize investments, and align execution with business outcomes
Team builder & mentor: Experience scaling teams, developing leaders, and creating a culture of technical excellence
Technical credibility: Strong foundation in ML/AI with applied expertise in generative AI, LLMs, RAG, or multi-agent systems
Enterprise-scale delivery: Experience integrating AI into production systems with cloud-native architectures (AWS, Azure, GCP)
Influence & communication: Exceptional ability to engage executives, engineers, and customers with clarity and impact
Experience with AI/LLMOps platforms, orchestration frameworks, and lifecycle management
Domain knowledge in networking, SD-WAN, or observability
Recognized contributions to the AI ecosystem (open-source projects, patents, or industry thought leadership)
Partnerships with academia, startups, or AI vendors to accelerate innovation
Skills
LLMs
RAG
AWS
Azure
GCP
AI/LLMOps
Introduction
At our Extreme, we create effortless networking experiences that empower people and organizations to advance. We are seeking a Director of AI Engineering to lead the design, development, and delivery of our next-generation AI-native systems.
About the role
This role requires a proven leader who combines technical depth with organizational vision. 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.
Key Responsibilities
Leadership & Vision
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Define the AI engineering vision and long-term roadmap; ensure alignment with business strategy and customer outcomes.
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Build, inspire, and scale a world-class AI engineering team, cultivating a culture of innovation, collaboration, and execution.
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Mentor senior engineers and emerging leaders, raising the technical and leadership bar across the organization.
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Champion responsible AI practices and set quality standards for reliability, ethics, and compliance.
End-to-End Productization
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Drive the full lifecycle of AI systems: from research exploration and prototyping through enterprise-scale production launches.
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Ensure seamless integration of AI into core products, balancing cutting-edge innovation with pragmatic delivery.
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Establish and enforce best practices for deployment, monitoring, and lifecycle management of AI systems in production.
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Measure impact and ensure that AI solutions deliver tangible business value.
Technical Leadership
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Provide architectural direction for scalable AI systems leveraging LLMs, multi-agent systems, and generative models.
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Guide technical decisions, ensuring systems are reliable, secure, and cloud-native.
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Evaluate emerging technologies and frameworks; make informed adoption decisions that strengthen competitive differentiation.
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Maintain enough hands-on involvement to earn respect from engineers, while staying focused on strategic leadership.
Cross-Functional & External Influence
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Partner with product management, engineering, and network experts to define and deliver AI-driven features.
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Communicate strategy, progress, and impact to executives, customers, and partners with clarity and influence.
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Represent the company externally as a thought leader in AI, contributing to industry forums, open-source communities, and customer engagements.
Qualifications
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A degree in Computer Science, Artificial Intelligence, or a related field (or equivalent practical experience).
•
Proven leadership track record: 12+ years in AI/ML engineering, including 5+ years in senior leadership roles managing teams and large-scale initiatives.
•
End-to-end product launch expertise: Demonstrated success leading AI initiatives from concept through production deployment and adoption at enterprise scale.
•
Strategic leadership: Ability to define AI roadmaps, prioritize investments, and align execution with business outcomes.
•
Team builder & mentor: Experience scaling teams, developing leaders, and creating a culture of technical excellence.
•
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.
•
Enterprise-scale delivery: Experience integrating AI into production systems with cloud-native architectures (AWS, Azure, GCP).
•
Influence & communication: Exceptional ability to engage executives, engineers, and customers with clarity and impact.
Nice to Have:
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Experience with AI/LLMOps platforms, orchestration frameworks, and lifecycle management.
•
Domain knowledge in networking, SD-WAN, or observability.
•
Recognized contributions to the AI ecosystem (open-source projects, patents, or industry thought leadership).
•
Partnerships with academia, startups, or AI vendors to accelerate innovation.