Director of AI Engineering – Generative AI & Autonomous Systems (10033) Seattle, WA

Seattle, Washington
Products – Engineering /
Fulltime /
Hybrid
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.