Senior Technical Product Manager – AI & Network Infrastructure

Verizon•Basking Ridge, NJ

10d•Hybrid

About The Position

We are looking for a forward-thinking, hands-on Technical Product Development Manager to direct the growth and strategic expansion of our next-generation Network Automation. This role combines technical leadership with strategic business acumen to build and launch advanced AI products and enterprise services. The ideal candidate brings a comprehensive understanding of AI industry trends, commercial models, and corporate strategy, backed by deep expertise in AI architectures, model frameworks, and agentic systems. Strong familiarity with Edge computing, Cloud environments, Data Centers, and AI-focused NeoClouds is required. Key requirements include hands-on expertise with agentic AI runtime infrastructure (such as AI Gateways, Routers, MCPs, and Semantic Caching) across Cloud, Edge, Data Center, and NeoCloud environments, along with a strong foundation in software-defined networking paradigms like SD-WAN and SASE.

Requirements

Bachelor’s degree or four or more years of work experience.
Six or more years of relevant experience required, demonstrated through one or a combination of work and/or military experience, or specialized training.
Five or more years of technical product management/development experience delivering enterprise-grade networking or AI software platforms.
Strong conceptual and technical foundation in DIA, EVPL, MPLS, SD-WAN, SASE, zero-trust security, or high-density data center network architectures.
Hands-on experience developing AI solutions across Edge, Cloud, traditional Data Centers, or specialized AI NeoClouds (GPU-as-a-Service).
Experience quickly prototyping, testing, and validating technical concepts in lab and multi-cloud environments before scaling to production.
Demonstrated success analyzing market trends and customer requirements to drive GTM strategy.
Willingness to travel up to 10%.

Nice To Haves

Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or a related field.
Knowledge of AI Gateways, AI Routers, vector/semantic caching mechanisms, and context standards like the Model Context Protocol (MCP).
AI market trend analysis including unit economics (GPU/token costs), AI services, prices and GTM strategies.
Hands-on familiarity with agentic frameworks, knowledge graphs, and context retrieval pipelines.

Responsibilities

Drive the convergence of enterprise WAN topologies—specifically SD-WAN and SASE frameworks—into a unified AI Fabric optimized for high-throughput, low-latency East-West and North-South traffic flows.
Architect and productize AI services, including AI Gateways, intelligent AI Routers, token brokering, token monitoring, standardized Model Context Protocols (MCPs) for context retrieval, and low-latency Semantic Caching layers.
Apply AI technologies to automate operations, optimize service delivery, and advance capabilities toward fully autonomous networks.
Demonstrated expertise in architecting and deploying scalable AI platform infrastructure to support agentic services. Proficient in agent identification, orchestration frameworks, as well as real-time intelligence and monitoring.
Lead end-to-end design and execution of AI Proof of Concepts (PoCs) in public cloud and lab environments.
Benchmark network performance, prompt/response latency, GPU utilization, and context-fabric efficiency under real-world AI inference and training workloads.
Formulate product roadmaps and commercial models based on deep market analysis of public hyperscalers, edge nodes, on-premise data centers, and GPU-first NeoClouds.
Monetize fabric capabilities by defining service levels (SLAs), enterprise security frameworks, and API/MCP integrations for autonomous agent workflows.