Jobs at Extreme Networks

Leads complex customer-facing engineering engagements involving intelligent networking, generative AI, automation, enterprise integrations, distributed systems, and cloud infrastructure. Designs architectures, writes production software, resolves high-risk technical challenges, establishes reusable engineering standards, identifies platform gaps, and guides product requirements. Serves as a senior escalation point, mentors engineers, and owns technical outcomes from discovery through production readiness.

Designs, builds, deploys, and stabilizes production software solutions directly with strategic customers. Responsibilities span applications, agentic AI, APIs, integrations, data, automation, networking, cloud infrastructure, testing, CI/CD, observability, and infrastructure-as-code. The engineer troubleshoots complex systems, supports production readiness, documents solutions, identifies reusable engineering patterns, and partners with Product teams to address platform gaps.

Lead customer-facing technical engagements from discovery and architecture through deployment and production readiness. Design, build, integrate, test, and stabilize production software involving AI, automation, data, networking, cloud infrastructure, APIs, and enterprise systems. Provide technical leadership, mentor engineers, conduct design and code reviews, create operational documentation, identify reusable patterns, and partner with Product teams to address platform gaps.

Lead architecture and development of scalable, secure, cloud-native software platforms for intelligent networking, distributed data processing, real-time analytics, and AI agent experiences. Design high-volume, low-latency systems; guide software development across the full lifecycle; mentor engineers; and solve complex technical problems involving microservices, network telemetry, cloud infrastructure, and generative AI.

Design, build, and operate GenAI and ML systems for network intelligence. Lead architecture of distributed ML services, implement REST APIs, containerize and deploy with Kubernetes, mentor engineers, and support LLM fine-tuning, retrieval-augmented generation, and big-data workflows.

Lead the design and development of machine learning solutions, overseeing the entire software development lifecycle and mentoring engineers. Drive innovation in Generative AI and high-performance systems.

Lead design and development of cloud-native, real-time distributed systems that process large volumes of network telemetry and power generative AI/agentic automation. Architect, implement, and operate scalable, reliable, and secure microservices and data platforms; mentor engineers and translate complex problems into production-ready solutions.

Lead design and delivery of cloud-native, real-time distributed platforms for intelligent networking and agentic AI. Architect scalable, secure systems processing high-volume network telemetry, mentor engineers, drive production deployments, and solve complex ambiguous problems across networking, AI, and data domains.

Design and implement scalable, secure cloud-native platforms and services for real-time network data processing, generative AI and agentic systems. Lead architecture, mentor engineers, build production-grade distributed systems for analytics, telemetry, and intelligent automation.

Build end-to-end internal AI-powered tools and systems using agentic coding workflows. Own full-stack development: backend services, pipelines, frontends, CI/CD, cloud deployments, MCP integrations, and dashboards to enable AI-assisted engineering across the company.

Leads the design, development, deployment, and operation of scalable machine learning solutions and high-performance microservices. Builds real-time inference systems using Triton and TensorRT, guides distributed cloud architectures, participates hands-on in coding and reviews, and mentors engineers. Drives technical strategy, operational excellence, system resilience, and business-wide innovation across generative AI, graph machine learning, and big data initiatives.