About NetBox Labs: NetBox Labs is a high-growth infrastructure software company on an ambitious mission to help enterprises build, scale, and manage complex modern networks. We accelerate the journey to comprehensive network automation by delivering open, composable open-source products and actively supporting a vibrant global networking community. NetBox Labs serves as the official commercial steward of NetBox—the world’s most popular network source of truth—and Orb, a next-generation open-source network observability framework. Backed by prominent venture institutions including Notable Capital (formerly GGV), Flybridge, IBM, and Salesforce Ventures, our enterprise self-managed and scalable cloud-hosted SaaS environments power thousands of tech-driven companies globally.
We are seeking a highly autonomous, channel-fluent, and commercially aggressive Sales Development Representative to accelerate net-new logo acquisition and revenue pipelines under a permanent, full-time remote configuration within the United Kingdom. Operating as an essential pipeline architect within our Revenue and Lead Generation vertical, you will manage multi-channel outbound campaign strategies targeting senior infrastructure and network decision-makers. Shifting completely away from routine non-regulated data transcription loops, entry-level website styling fixes, or general helpdesk customer support ticketing, you will run an active multi-tenant cold outreach, prospect account qualification, and technical interest generation laboratory. Partnering directly neben core corporate account executives and sales leaders, you will translate abstract enterprise infrastructure challenges into qualified discovery opportunities. This position requires an engineering-minded inbound and outbound closer with 1+ years of software sector history who handles B2B prospecting fluidly natively using Sales Representative, Lead Generation, and Cold Calling primitives, crafts messages that resonate deeply with engineering buyers, and exceeds outbound conversion thresholds autonomously.
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