Director of AI Engineering at Extreme Networks, leading the design and delivery of AI-native systems. Driving enterprise-level AI solutions for networking optimization, security, and support.
Responsibilities
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.
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.
Requirements
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.
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