Lead 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:

GTM at Mews runs on Salesforce, HubSpot, Nue, Databricks and Gong, and a lot of the work between those systems is still manual. This role owns the answer to a question that did not exist as a job a year ago: can we build this with AI instead of buying another tool. It is the first role of its kind at Mews, with no playbook to inherit and no predecessor to follow.

You will sit close to GTM teams, understand how they actually work, and ship production automation that removes manual steps from the commercial stack. This is IC5, the most senior individual contributor level at Mews, and it is a pure IC track with no path or expectation into people management.

What you would do

• Meet with GTM teams to understand their processes firsthand, then design and ship automation that removes real manual work
• Own delivery end to end: no PM, no handoff, you scope, build, and validate what you ship
• Travel to local offices when deeper embedding is needed, build alongside the team for a few days, and train them on what you shipped
• Architect systems that integrate with Salesforce, HubSpot, Nue, Databricks and Gong, with security and reliability built in from the start
• Work as the connective layer between engineering rigor and commercial reality, translating GTM problems into production-grade AI systems

AI Fluency Level 4: this role is built around it. You will design and ship AI-powered systems that GTM teams depend on for real commercial outcomes, not internal prototypes. That means making engineering decisions about model choice, agent design, and RAG pipelines the same way you would about any other production system, and taking full ownership of what happens when it is live.

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

• 5 to 7+ years of engineering experience at Tech Lead, Staff, or Principal level, with a track record of owning a technical domain end to end at a company between 100 and 2,000 people
• The last 6 to 12 months spent heavily on AI: building agents, shipping AI-built systems to production, with concrete proof of impact rather than demos
• Genuine fluency with LLM APIs, agent frameworks, RAG pipelines, and MCP integrations, as an active practitioner rather than an occasional user
• Deep engineering judgment: you can validate AI-generated code, reason about security and architecture, and are comfortable in any language rather than tied to one tool or platform
• AI Fluency Level 4 or the equivalent hands-on experience shipping AI-powered systems into production

Nice to have

• Some Salesforce or CRM engineering experience, beyond admin or low-code configuration
• Familiarity with the GTM stack: HubSpot, Nue, Databricks, Gong, Clay
• Comfort working directly with RevOps or sales ops stakeholders without needing a translator

Spain

€68.500—€103.000 EUR

Czechia

1 327 000 Kč—2 399 000 Kč CZK

UK

£78,500—£125,000 GBP

Sweden

705 500 kr—1 165 500 kr SEK

Ireland

€75.500—€125.000 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.