<div><b>Introduction</b><span> </span></div><div><span>At our Extreme, we create effortless networking experiences that empower people and organizations to advance. We are seeking a </span><b>Director of AI Engineering</b><span> to lead the design, development, and delivery of our next-generation AI-native systems. </span></div><div><span>This role requires a </span><b>proven leader who combines technical depth with organizational vision</b><span>. 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. </span></div><h3>Key Responsibilities </h3><ul><li><br /></li><div><b>Leadership &amp; Vision </b></div><li>Define the AI engineering vision and long-term roadmap; ensure alignment with business strategy and customer outcomes. </li><li>Build, inspire, and scale a world-class AI engineering team, cultivating a culture of innovation, collaboration, and execution. </li><li>Mentor senior engineers and emerging leaders, raising the technical and leadership bar across the organization. </li><li>Champion responsible AI practices and set quality standards for reliability, ethics, and compliance. </li><div><br /></div><div><b>End-to-End Productization </b></div><div><br /></div><li>Drive the full lifecycle of AI systems: from research exploration and prototyping through enterprise-scale production launches. </li><li>Ensure seamless integration of AI into core products, balancing cutting-edge innovation with pragmatic delivery. </li><li>Establish and enforce best practices for deployment, monitoring, and lifecycle management of AI systems in production. </li><li>Measure impact and ensure that AI solutions deliver tangible business value. </li><div><br /></div><div><b>Technical Leadership </b></div><div><br /></div><li>Provide architectural direction for scalable AI systems leveraging LLMs, multi-agent systems, and generative models. </li><li>Guide technical decisions, ensuring systems are reliable, secure, and cloud-native. </li><li>Evaluate emerging technologies and frameworks; make informed adoption decisions that strengthen competitive differentiation. </li><li>Maintain enough hands-on involvement to earn respect from engineers, while staying focused on strategic leadership. </li><div><br /></div><div><b>Cross-Functional &amp; External Influence </b></div><div><br /></div><li>Partner with product management, engineering, and network experts to define and deliver AI-driven features. </li><li>Communicate strategy, progress, and impact to executives, customers, and partners with clarity and influence. </li><li>Represent the company externally as a thought leader in AI, contributing to industry forums, open-source communities, and customer engagements. </li></ul><h3>Qualifications </h3><ul><li>A degree in Computer Science, Artificial Intelligence, or a related field (or equivalent practical experience). </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. </li><li>End-to-end product launch expertise: Demonstrated success leading AI initiatives from concept through production deployment and adoption at enterprise scale. </li><li>Strategic leadership: Ability to define AI roadmaps, prioritize investments, and align execution with business outcomes. </li><li>Team builder &amp; mentor: Experience scaling teams, developing leaders, and creating a culture of technical excellence. </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. </li><li>Enterprise-scale delivery: Experience integrating AI into production systems with cloud-native architectures (AWS, Azure, GCP). </li><li>Influence &amp; communication: Exceptional ability to engage executives, engineers, and customers with clarity and impact. </li></ul><h3>Nice to Have:</h3><ul><li>Experience with AI/LLMOps platforms, orchestration frameworks, and lifecycle management. </li><li>Domain knowledge in networking, SD-WAN, or observability. </li><li>Recognized contributions to the AI ecosystem (open-source projects, patents, or industry thought leadership). </li><li>Partnerships with academia, startups, or AI vendors to accelerate innovation. </li></ul>

Extreme Networks

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

Extreme Networks