GTM Automation Engineer - AI-Driven

HiveMQ is the Industrial AI Platform helping enterprises move from connected devices to intelligent operations. Built on the MQTT standard and a distributed edge-to-cloud architecture, HiveMQ connects and governs industrial data in real time, enabling global leaders like Audi, BMW, Eli Lilly, and Siemens to operationalize AI and drive innovation at scale.

At HiveMQ, our culture is Effortless → Empowered → Relentless. We make the complex simple, act with confidence and ownership, and never stop pushing the boundaries of what’s possible. Join us to power the future of intelligent industry.

We have a proven enterprise sales motion and we're building a product-led growth engine alongside it. Between those two motions sits a gap in path to revenue. This role exists to close that gap with systems, not headcount. You'll build the infrastructure that takes every inbound signal - product signup, form fill, trial activity - and turns it into a routed, enriched, nurtured, and qualified lead before it ever touches a human.

You'll deploy AI agents that do the research, qualification, and follow‑up work that doesn't scale manually. And you'll define what the transactional path to close looks like at HiveMQ when an AE isn't the right answer. After solving this, you will move further down the funnel to solve other marketing, sales, and revenue challenges across our GTM motions. If you're the kind of person who sees a broken funnel and starts mentally sketching the fix before the conversation ends, this role was written for you.

• 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 - replacing manual processes with autonomous workflows.

• 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 Hub Spot, Salesforce, Clay, Default, Slack, G‑suite, and more that connects demand to revenue at every segment.

• Build enrichment pipelines that surface firmographic, technographic, and product context before the first human touchpoint - no manual research.

• Build agentic AI support layer across marketing and sales functions.

• Partner with Marketing, Demand Gen, Sales, and GTM Ops to translate operational bottlenecks into engineered, automated solutions.

• 2–4 years of experience in GTM engineering, marketing operations, or revenue operations - with a track record of building systems, not just configuring them. Also considering high‑agency individuals with relevant experience passionate in moving this career direction.

• Hands‑on experience with Hub Spot 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…