GTM Engineer

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HiveMQ

Site WebLinkedInTous les Emplois

51 - 200 employés

Fondée en 2012

☁️ SaaS

🏢 Entreprise

🤝 B2B

💰 Venture Round - HiveMQ en 2025-01

SaaS • Enterprise • B2B

HiveMQ est une entreprise de logiciels qui fournit une plateforme de données en temps réel basée sur MQTT pour diffuser, contextualiser, régir et agir sur la télémétrie opérationnelle des dispositifs en périphérie jusqu'aux systèmes d'entreprise. Son portefeuille de produits comprend une offre gérée dans le cloud (HiveMQ Cloud), un courtier MQTT auto-géré, des passerelles edge, un hub de données et des outils d'analyse pour permettre des charges de travail IoT et industrielles critiques et toujours disponibles. HiveMQ sert principalement les clients d'entreprise dans la fabrication, l'énergie, les centres de données, le transport et d'autres industries, permettant des déploiements SaaS B2B qui alimentent les flux de travail d'IA et d'analytique avec des données de confiance, en temps réel.

Description

• Own the end-to-end inbound and PLG funnel infrastructure - from first product signal or form fill to the right next step - ensuring every lead is enriched, scored, and routed into the right GTM motion without manual triage. • Build automated paths for transactional and mid-market demand that don't require AE time: self-serve, low-touch sequences, and AI-assisted qualification that moves leads toward close independently. • Deploy agentic AI systems across marketing functions - research, lead qualification, personalized follow-up, meeting booking. • Design and operate lead qualification models that route leads to the right GTM motion based on first- and third-party signals, product usage, firmographics, behavioral data, and more. • Build pre-AE qualification and nurture infrastructure so leads that reach a rep are warm, educated, and ready - not raw inbound that eats selling time. • Build and maintain the orchestration layer across HubSpot, Salesforce, Clay, Default, Slack, G-suite, and more that connects demand to revenue at every segment. • Build agentic AI support layer across marketing and sales functions. • Deploy AI agents that do the research, qualification, and follow-up work that doesn't scale manually. • Define what the transactional path to close looks like at HiveMQ when an AE isn't the right answer.

🎯 Exigences

• 2–4 years of experience in GTM engineering, marketing operations, or revenue operations - with a track record of building systems, not just configuring them. • Hands-on experience with HubSpot and Salesforce as a CRM system of record. • Practical fluency with enrichment and automation tooling - Clay, Clearbit, Default, Hubspot, or comparable platforms. • Experience building or deploying AI agents or LLM-powered workflows (Claude Code, Codex, etc.) in a GTM or revenue context - not just prototypes, but trusted systems that run in production at scale. • Comfort with APIs, webhooks, and light scripting (Python or JavaScript) to build around vendor limitations when off-the-shelf output isn't good enough. • Comfort with large data sets used to inform GTM engineering and workflows in AWS, GBQ, etc. • Experience building lead qualification and routing logic - scoring, segment-based routing, SLA definition and enforcement. • A systems mindset: you think about edge cases, failure modes, and what happens at 10x volume before you ship. • The autonomy to move from concept to production in a remote environment without constant oversight.

🏖️ Avantages

• No manual processes with autonomous workflows. • Build enrichment pipelines that surface firmographic, technographic, and product context before the first human touchpoint - no manual research. • Partner with Marketing, Demand Gen, Sales, and GTM Ops to translate operational bottlenecks into engineered, automated solutions.