Senior AI Engineer building autonomous agent features and evaluation infrastructure. Improving Monte Carlo's platform for observing, troubleshooting, and trusting production AI systems.
EN
Director of AI Engineering – Generative AI, Autonomous Systems
Posted last month
About the role
- 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.
Benefits
- health insurance
- retirement plans
- paid time off
- flexible work arrangements
- professional development
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