Director of AI Engineering – Generative AI & Autonomous Systems (10033) Toronto, Canada
extremenetworks
Toronto, Canada
Posted Sep 24, 2025
- Full-time
- Products
Job description
**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. 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** - Define the AI engineering vision and long-term roadmap; ensure alignment with business strategy and customer outcomes. - Build, inspire, and scale a world-class AI engineering team, cultivating a culture of innovation, collaboration, and execution. - Mentor senior engineers and emerging leaders, raising the technical and leadership bar across the organization. - Champion responsible AI practices and set quality standards for reliability, ethics, and compliance. **End-to-End Productization** - Drive the full lifecycle of AI systems: from research exploration and prototyping through enterprise-scale production launches. - Ensure seamless integration of AI into core products, balancing cutting-edge innovation with pragmatic delivery. - Establish and enforce best practices for deployment, monitoring, and lifecycle management of AI systems in production. - Measure impact and ensure that AI solutions deliver tangible business value. **Technical Leadership** - Provide architectural direction for scalable AI systems leveraging LLMs, multi-agent systems, and generative models. - Guide technical decisions, ensuring systems are reliable, secure, and cloud-native. - Evaluate emerging technologies and frameworks; make informed adoption decisions that strengthen competitive differentiation. - Maintain enough hands-on involvement to earn respect from engineers, while staying focused on strategic leadership. **Cross-Functional & External Influence** - Partner with product management, engineering, and network experts to define and deliver AI-driven features. - Communicate strategy, progress, and impact to executives, customers, and partners with clarity and influence. - Represent the company externally as a thought leader in AI, contributing to industry forums, open-source communities, and customer engagements. ### Qualifications - 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: - 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.