Staff SW Systems Engineer -Agentic Product Engineer

Job description

Over 50,000 customers globally trust our end-to-end, cloud-driven networking solutions. They rely on our top-rated services and support to accelerate their digital transformation efforts and deliver unprecedented progress. With double-digit growth year over year, no provider is better positioned to deliver scalable outcomes than Extreme. Inclusion is one of our core values and in our DNA. We are committed to fostering an inclusive workplace that embraces our differences and creates an atmosphere where all our employees thrive because of their differences, not in spite of them. Become part of Something big with Extreme! As a global networking leader, learn why there’s no better time to join the Extreme team. **Position : Agentic Product Engineer /Staff SW Systems Engineer** **Experience : 8 to 14 Years Experience** **Skills : Python,TypeScript or JavaScript,AI coding agents Claude Code, Copilot, Cursor, Anthropic SDK or Microsoft Agent Framework or LangGraph, MCP (Model Context Protocol)** Why Join Extreme Networks There has never been a better time to join Extreme Networks. Through strategic acquisitions and an expanded go-to-market strategy, we have significantly broadened our portfolio and unlocked tremendous opportunities for growth across regions. Recognized as a Technology Leader in the Gartner Magic Quadrant, Extreme is equally committed to building an inclusive, people-first culture. Diversity, inclusion, and equality are core to who we are. We believe employees thrive because of their differences — not despite them — and we are proud to foster an environment where every Extremist can do their best work. Come become part of something big with us. We are a global leader, with hubs in North America, South America, Asia Pacific, Europe, and the Middle East. About This Team We are a newly formed, small, high-impact team with a strategic mandate: accelerate Extreme’s adoption of AI-assisted ways of working across the company. We design and build internal AI-powered tools and systems used by Extreme’s engineering and business teams to move faster, with higher quality. The team reports directly to senior executive leadership. You will work closely with the team lead and alongside a small group of engineers with high ownership over what gets built and shipped. About the Role You are a full-stack builder who takes a spec and owns it end-to-end: design, implementation, testing, and deployment. You work with AI coding agents as your primary execution tool — not autocomplete, but agentic workflows where you direct, evaluate, and iterate on agent-generated output to ship production-grade software faster and with higher quality. This is not a specialization role. You own your surface from inception to production. Backend APIs, data pipelines, lightweight frontends, GitHub Actions workflows, cloud deployment — you handle the full lifecycle without handoffs. What You Will Build You will build internal AI-powered tools and systems that help Extreme’s engineering and business teams do their best work. This includes: - AI workflow infrastructure: Automation, integrations, and governance harnesses that enable teams to adopt and operate AI-assisted development workflows — connecting GitHub, Jira, and Confluence into structured, repeatable pipelines - Internal dashboards: Tools that help engineering teams track quality and progress on their own AI-assisted work - MCP servers and integrations: Organizational knowledge exposed to AI coding agents via Model Context Protocol — enabling agents to query internal systems in real time Qualifications - 8+ years of professional software engineering experience, with a track record of shipping production systems - Python and TypeScript/JavaScript — backend services, pipelines, frontends, and automation - CI/CD experience building pipelines and automated workflows (GitHub Actions) - Cloud fundamentals (AWS or Azure) — enough to deploy what you build - Production experience with AI coding agents (Claude Code, GitHub Copilot, Cursor, or equivalent) — agentic sessions, not just autocomplete - Experience with agent frameworks: Anthropic SDK, Microsoft Agent Framework, or equivalent - Familiarity with MCP (Model Context Protocol) - Familiarity with RAG pipelines, Knowledge Graphs and vector databases - Experience building internal tooling adopted by large engineering organizations What Success Looks Like at 90 Days - You have shipped at least two production features end-to-end - The agent context documentation for your assigned surfaces is comprehensive enough that a new team member’s agent generates correct output from it on first use - You are operating with minimal supervision on new problem statements