Director of Engineering -Exchange

Extreme Networks•San Jose, CA

24d•$175,000 - $260,000

About The Position

This role is an incredible opportunity to work at the forefront of AI-driven networking, agentic automation, cloud-native platforms, and intelligent product experiences. You will help lead the development of a next-generation platform that enables an ecosystem of AI agents, tools, skills, and integrations designed to support highly scalable, secure, reliable, and adaptable enterprise use cases. Extreme Networks is a global networking leader and a Technology Leader in the Gartner Magic Quadrant, deeply committed to fostering a culture that embraces diversity, inclusion, and equality in the workplace. The company is driving a fundamental shift in how businesses manage wired and wireless networks by building high-performance, real-time systems that can perceive, reason, retrieve context, use tools, and take intelligent action on behalf of users. You will lead engineering teams working on strategic AI platform capabilities, including agent orchestration, tool and skill ecosystems, secure integration frameworks, scalable microservices, and enterprise-grade runtime infrastructure. You will partner closely with product, architecture, security, cloud operations, and other engineering leaders to define the technical direction and deliver high-impact systems that are reliable, extensible, and built for long-term scale.

Requirements

Bachelorâ€™s degree in Computer Science, Engineering, Machine Learning, Mathematics, or a related technical discipline, or equivalent practical experience.
15+ years of software engineering experience, including 10+ years of engineering leadership experience and 5+ years managing managers or multiple engineering teams.
Proven track record of designing, delivering, and operating complex, high-impact AI, ML, generative AI, automation, or intelligent software platforms.
Strong practical understanding of generative AI and agentic architectures, including LLM integration, Model Context Protocol, RAG, agents, tools, skills, orchestration, context/memory, evaluation, guardrails, observability, and policy controls.
Experience leading teams that build scalable, secure, and reliable cloud-native AI or dataintensive services, with strong depth in distributed systems, microservices, APIs, and production operations.
Experience managing multiple concurrent programs and engineering teams in an Agile or iterative product development environment.
Strong communication skills with the ability to engage effectively with executives, product leaders, architects, senior engineers, security teams, and cross-functional stakeholders.

Nice To Haves

MS or PhD in Computer Science, Artificial Intelligence, Machine Learning, Distributed Systems, or equivalent experience.
Experience with agentic AI platforms, AI agent frameworks, tool-use systems, MCP-style integrations, plugin ecosystems, workflow automation, developer platforms, or skill marketplaces.
Experience building or leading extensible platforms where multiple teams, services, or partners contribute capabilities through APIs, SDKs, plugins, tools, integrations, or developer-facing interfaces.
Experience designing secure, governed platforms that support permissions, tenant isolation, auditability, rate limiting, policy controls, observability, and safe tool execution.
Experience with cloud platforms and modern infrastructure technologies such as AWS, Azure, GCP, Kubernetes, Docker, Kafka, SQL/NoSQL databases, search systems, vector databases, graph databases, or event streaming platforms.
Experience partnering with Product Management and Program Management to define strategy, clarify requirements, manage trade-offs, and deliver customer-facing platform capabilities.

Responsibilities

Provide visionary technical and organisational leadership for teams building next-generation AI agent platforms, tool ecosystems, and cloud-native services, including agent orchestration, tool invocation, skill discovery, workflow execution, context management, and governance.
Define and drive the engineering roadmap for highly scalable, secure, reliable, and extensible systems that enable AI agents, tools, skills, integrations, and enterprise workflows across Extremeâ€™s product portfolio.
Build, mentor, and lead high-performing teams, including hiring, performance management, developing leaders, and fostering a culture of strong engineering standards, accountability, and innovation.
Drive execution across multiple programs and teams, ensuring clear priorities, predictable delivery, effective risk management, and alignment with product, architecture, security, CloudOps, and senior leadership.
Guide complex architectural and technical decisions, including trade-offs related to distributed systems, multi-agent workflows, latency, reliability, cost efficiency, tenant isolation, data privacy, and platform extensibility.
Champion production readiness and operational excellence, including secure-by-design development, API consistency, observability, SLOs, capacity planning, resiliency, automation, and measurable quality outcomes.
Stay current with emerging AI and platform trends, including agent frameworks, MCPbased tooling, skill ecosystems, RAG patterns, LLM integration, evaluation, guardrails, and enterprise AI governance.