Director of Engineering -Exchange

Job Responsibilities

• Provide visionary technical and organizational 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 Extreme’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, MCP-based tooling, skill ecosystems, RAG patterns, LLM integration, evaluation, guardrails, and enterprise AI governance.

Basic Qualifications

• Bachelor’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 data-intensive 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.

Preferred Qualifications

• 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.