Senior GTM System Builder

Help make the world more hospitable The hospitality industry is uniquely human, and it deserves technology that’s just as inspiring as the people behind it. At Mews, we’re transforming the industry with a platform that helps hotels run smarter, move faster and create better guest experiences. You’ll work with smart, curious people who care deeply about what they do. You’ll have autonomy and the trust to make good decisions and move quickly. And you’ll enjoy a real sense of purpose as you see the impact of what we’re building. If you’re motivated by ownership, curiosity and meaningful impact, and are driven to deliver consistent high performance, you’ll feel at home here.

About the role

Let's get into the specifics. It’s impossible to capture every nuance of a role – especially at a rapidly growing company like Mews – but if we had to distil it into a job description (which we do because this is a job description), it would be this: The commercial team at Mews moves deals through a complex, multi-touch GTM motion. The person in this role owns the systems that make that motion faster, smarter, and less dependent on manual effort — from inbound routing and deal enrichment to Gong-driven coaching intelligence and CPQ automation. This is not a support role for the commercial team. It is an ownership role for the infrastructure they run on. You will join the Growth team to own an assigned domain within the GTM stack end to end: scoping, building, shipping, and running production systems that move ARR. You will work under staff technical direction but make your own architecture and build-vs-buy decisions within your domain. You will manage vendor relationships, define observability standards, and be the person who picks up the phone when something breaks in production. What you would do Own the full lifecycle of automation and AI-tooling initiatives within your assigned GTM pod: scoping, building, shipping to production, and iterating based on adoption and KPI data — not just ticket completion Build and ship AI-powered pipelines that permanently remove manual GTM work: deal enrichment, outbound research and routing, Gong-driven coaching signals, forecasting inputs, CPQ automation, and proposal follow-up Design the prompting architecture and agent logic that commercial reps, BDRs, and AEs interact with daily — reliable outputs for non-technical end users, with observability and error handling built in from the start Own operational health of your domain's live systems: first responder when things break, with adoption metrics, error rates, and data quality visibility instrumented before deployment Manage vendor relationships at pod level (Gong, Clay, LeanData, ZoomInfo, depending on assignment): SLAs, incident escalation, business reviews, and periodic build-vs-buy re-decisions Support other engineers through code review, pairing, and coaching on architecture trade-offs — and contribute reusable patterns and integrations that accelerate delivery across pod AI Fluency Level 4: In this role, AI is not a productivity layer — it is the product. You will architect and ship LLM-powered agents, enrichment pipelines, and AI-assisted automations that the commercial org depends on. You will make engineering decisions about models, infrastructure, and MCP integrations. You will design prompting systems that non-technical users rely on without ever touching a prompt themselves. The test for everything you build is whether a KPI moved — which means your judgment about where AI is trustworthy and where it needs a human in the loop is part of the work, not an afterthought. For more information on AI fluency at Mews, please refer to AI Fluency at Mews: A Comprehensive Guide for Candidates on Confluence. What you would bring 4 to 6 years delivering production software with measurable commercial impact in a product-driven company (high-growth SaaS, startup, or scale-up) Demonstrated end-to-end ownership with strong autonomy: you have defined the approach, navigated genuine ambiguity, and owned the outcome — not executed tickets Has shipped AI-powered pipelines or agents in a real operational context: enrichment, routing, summarization, or AI-assisted automation — not just prototypes Active practitioner of modern AI development tooling (Claude, Lovable, Cursor, or equivalent) and comfortable working with LLM APIs and MCP integrations — AI Fluency Level 4 or the equivalent hands-on engineering experience Hands-on experience building against Salesforce or equivalent CRM APIs: workflows, event-driven logic, and data integrations across multiple systems Comfortable owning live production systems: incident response, observability, vendor management, and data integrity — draws no hard line between building and running Can translate operational pain into technical requirements and explain technical decisions clearly to non-technical stakeholders Nice to have Experience in or alongside a RevOps or GTM function — understands what commercial reps actually need, not the idealized version Hands-on experience with Gong API, Clay, LeanData, or ZoomInfo integrations Familiarity with Nue/CPQ, Databricks, HubSpot, Hook, or Ada Spain €53.500 — €84.000 EUR Czechia 1 008 000 Kč — 1 632 000 Kč CZK UK £59,000 — £85,692 GBP Sweden 570 500 kr — 949 000 kr SEK Ireland €61.000 — €100.000 EUR Pay Transparency at Mews Salary ranges are provided in good faith and reflect current market conditions and internal pay structures. Final compensation may be adjusted based on funding, budget constraints, or exceptional candidate qualifications, but will remain within reasonable proximity to the stated range. This salary disclosure is provided in compliance with applicable pay transparency legislation. We are committed to equal pay practices and prohibit salary history inquiries during our recruitment process. If the location you're applying from wasn't originally advertised for this role, salary range information is avail