Over 50000 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.
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Product Manager AI/ML Product Builder (Core Intelligence)
Overview
Were hiring a hands-on AI/ML Product Builder to work on designing and delivering Extremes next generation of intelligence agents as we build towards the future of self-driving networks.
Youll be joining a team that is building the entire AI/ML stack end to end: from platform and pipelines to models agents and user-facing applications. This is a rare opportunity to shape the foundational intelligence layer across Extremes products and have immense organisation-wide and customer impact on how networks are monitored diagnosed and optimized.
This is a mid-level builder-oriented role for someone who combines strong product sense with the ability to effectively use AI as a tool (vibe coding rapid prototyping LLM workflows) and who understands how to build agentic systems that reason act evaluate and improve over time.
If you thrive at the intersection of AI/ML systems thinking and zero-to-one product building youll fit right in.
Key Responsibilities
Partner closely with the cross-functional and network SMEs to define and build AI/ML-powered agents that improve reliability performance and operational efficiency across Extremes network offerings.
Own the end-to-end lifecycle for intelligence capabilities: discovery scoping prototyping development launch iteration.
Use AI tools (LLMs copilots vibe coding) to prototype agent behaviours automations evaluators reasoning flows and UX interactions.
Work with engineering to design and ship agentic systems that perform multi-step reasoning take actions validate outcomes and learn from telemetry.
Translate raw telemetry events logs observed patterns and signals into clear models insights and agent behaviours.
Define agent policies triggers safety boundaries and success criteria.
Drive clarity for engineering with crisp product and outcome definitions evaluation frameworks.
Collaborate with design to create trustworthy explainable AI/ML experiences - especially for diagnostics troubleshooting and decision assistance.
Partner with AI/ML engineers to optimize model performance latency cost data quality and decision accuracy.
Build feedback loops and evaluation systems to continuously improve agents over time.
Ensure all intelligence features meet enterprise-grade safety privacy responsible AI and operational constraints.
Operate with urgency - simplify complexity unblock teams quickly and ship real value fast.
Qualifications
Proven experience building and shipping AI/ML features or agents (LLMs ML models anomaly detection predictive systems or autonomous workflows).
Quick learner with a builders mindset - able to ramp on new concepts stacks and domains rapidly and turn ambiguity into working prototypes.
Skilled at using AI as a force multiplier: vibe coding tools (Replit Copilot Windsurf) RAG & eval frameworks agent orchestration and fast prototyping.
Ability to read/write lightweight code or scripts in Python with AI assistance to accelerate prototyping.
Strong product instincts: simplifying complex technical domains prioritizing sharply and defining user value clearly.
Familiarity with LLM orchestration retrieval pipelines vector stores guardrails and cost/latency trade-offs.
Understanding of agentic patterns is a plus.
Experience working with telemetry logs and event streams to identify opportunities for intelligence and automation.
Excellent async communication we are a remote first company.
Experience in networking and/or security is a plus not required.
Comfortable operating in fast-paced ambiguous zero-to-one environments.
Experience
5 years in product management or PM/technical hybrid roles.
2 years building and shipping AI/ML solutions agents or intelligence capabilities end-to-end.
Portfolio or examples demonstrating:
- AI/ML features or agents shipped to production
- Rapid prototyping with AI tools
- Evaluation of model quality cost latency reliability
- Strong product thinking applied to complex or diagnostic domains