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AI GTM Engineer (RevOps)

Chainels
1 day ago
Full-time
Remote friendly (Rotterdam, NL)
Worldwide
Chainels is looking for its first in-house AI GTM Engineer to join the Rotterdam team. The company builds TenantOS for property managers and landlords, and City Connect for community managers in cities and business parks. It’s an AI-native, Claude-first business with a post-Series A profile that’s already trusted across more than 20 countries, powering thousands of communities and hundreds of thousands of users as it heads toward €10M ARR. This role is a hands-on mix of systems, data architecture, process improvement and stakeholder enablement, aimed at turning Marketing, Sales and Service into one coherent revenue engine.

The position is hybrid, based in or near Rotterdam with two days in the office. You’ll sit at the intersection of Marketing, Sales and Service, acting as the connector that aligns attribution, pipeline hygiene and customer health. The company already runs on HubSpot, n8n, Claude company-wide, Claude Code, and MCP servers, so you’ll step into a defined stack while shaping new connections. If you’re excited by clean data and practical AI-powered tooling, you’ll feel at home here.

This is a building role. The emphasis is on shaping the systems, processes and playbooks from scratch, while leveraging a foundation that’s already in place. HubSpot data is the backbone for every commercial decision, so you’ll own data quality and definitions from first touch through renewal. You’ll also develop AI-driven workflows that span enrichment, scoring, research and reporting, using Claude, MCP, n8n, Lemlist and Clay, and manage integrations that knit the stack together.

The day-to-day rhythm you’ll own blends technical mastery with practical process design. You’ll keep HubSpot as the central source of truth, maintaining pipelines, custom objects, lifecycle stages and the reporting that reveals real-time pipeline health and revenue movement. At the same time you’ll design and maintain cross-functional workflows so Marketing, Sales and Service operate in one smooth cadence, reducing handoffs and friction across the customer journey. Part of the job is building Claude skills, Projects and plugins that the commercial team relies on for pricing, quoting and competitive research, and setting up automations and lead scoring in collaboration with the marketing lead. You’ll also manage the integrations that connect HubSpot to the rest of the stack, using MCP as a bridging layer where it makes sense, so the whole revenue engine runs from a single source of truth.

What you’ll need to bring
Must-haves
- Three to five years in RevOps, GTM engineering or marketing/sales operations within B2B SaaS, with demonstrable impact.
- A data-first mindset: you model data, are comfortable with SQL, APIs and spreadsheets, and routinely reconcile numbers across systems to catch issues early.
- Deep HubSpot know-how: you don’t just use it, you architect it with workflows, custom objects, reporting and API integrations.
- Daily experience with Claude or a similar AI tool: you’ve built skills, Projects, MCP connections or agentic workflows, and you know when the AI output needs a human check.
- Practical hands-on experience with automation platforms (n8n, Make, or Zapier) and real workflows, not just tutorials.
- A systems-thinking approach that anticipates downstream effects and scales gracefully.
- Strong communication skills: you translate complex tech into business outcomes for leadership and work across technical and commercial teams.
- A proactive, hands-on mindset and willingness to pitch in as needed in a small team.
- Fluency in English and Dutch (written and spoken).
- Based in or near Rotterdam with the hybrid 2-days-in-office routine.

Nice-to-haves
- Experience in proptech, real estate or another niche B2B vertical.
- Comfort with high-ACV cycles and complex buying committees.
- A track record of building or scaling a RevOps function, ideally as the first hire.
- Familiarity with outbound/ABM tooling like Clay or Lemlist.
- Experience operating across European markets.
- Evidence of shipping Claude Code projects or building your own MCP server.

We offer
Chainels provides access to Claude for daily work and a budget to experiment with the latest AI tooling, plus a yearly personal development allowance to keep growing. The environment is international and fast-growing, with a salary and benefits package that includes a modern pension plan. The culture rewards results and shared learning from both successes and failures, and the hybrid setup supports collaboration and focus. You’ll receive a modern laptop and phone, and there are 25 days of annual leave, plus complimentary lunches at the office. Team outings, Friday drinks and occasional trips are part of the rhythm as the company grows. For context, the company is currently not hiring applicants who live outside of the EU.

Advice for applicants
Start your resume with a short note about RevOps and GTM engineering work you’ve led, emphasising how you integrated Marketing, Sales and Service using HubSpot, AI tooling and automation. Tie your experience to the 50% systems, data & architecture, 30% process optimization, 20% stakeholder enablement breakdown and show concrete results in pipeline health, MRR movement and churn definitions.

When you describe your must-have skills, include examples of end-to-end AI-driven workflows you built with Claude, MCP, n8n or similar tools, plus a real-world HubSpot architecture you designed or improved. If you have data modeling or API integration stories, share them and point to the impact on revenue metrics or forecast accuracy.

In interviews, be prepared to walk through how you would tackle a typical cross-team project, from data model and definitions to the automation blueprint and how you’d measure success. Have a concrete story ready about a friction point you eliminated in the customer journey or a cross-functional process you streamlined.

Ask a smart question such as: what would success look like in the first 90 days for this role, and which data quality gaps most hinder the revenue engine today? How are Claude-driven workflows prioritized, and what would you want the first AI project to achieve for attribution or forecasting?