Senior GTM System Builder

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