Mews
Director of Product and Engineering - Support
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Director of Product and Engineering for Support
As our Director of Product and Engineering for Support, you'll own how Mews decides whether to extend, migrate, or build its AI-powered self-service platform, and everything that makes that decision correct: the knowledge layer underneath it, the tooling agents rely on, and the feedback loop that turns customer contact into product change. Right now, contact volume is a signal Mews isn't fully using: every ticket implies something about product quality, and closing that loop is what this role exists to do.
You'll lead a tribe of 6–10 Product Builders, own the tradeoffs on tooling like Ada, Salesforce, and Aircall, and report to the Senior Director of Growth. This isn't a support-operations role, it's a build role with commercial teeth, in a company that ships fast enough that the loop between engineering decisions and customer contact is short and visible.
What you would do:
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- Own the AI-powered self-service platform, including the evaluation of whether Mews extends, migrates, or builds, and co-own operational standards (escalation protocols, severity definitions, SLA targets) with Support.
- Own product knowledge infrastructure: help content, release notes, agent-facing knowledge, and keep it accurate against a fast release cadence.
- Run build-vs-buy evaluations across the wider tooling landscape (Ada, Salesforce, Aircall, and others), with real commercial rigour, and execute when the call is to build.
- Own the product feedback loop: cluster tickets by root cause, weight by ARR exposure, and deliver findings to R&D in a format built to drive prioritisation.
- Track the impact of every product launch on contact volume, feeding that signal back before the next release cycle.
What you would bring:
- Substantial product and/or engineering experience, including recent years at senior/Director level overseeing cross-functional tribes in B2B SaaS at meaningful scale.
- Hands-on familiarity with LLM and RAG integration patterns and conversational AI evaluation, not just conceptual awareness.
- A track record owning self-service, AI-assisted resolution, or agent tooling, with a clear view of what good looks like for deflection, contact rate, and agent productivity.
- Build-vs-buy decisions made and lived with, backed by real commercial and product rigour.
- You've gone beyond personal productivity with AI: you've redesigned how a team works using it, built approaches others can follow, and you actively question and verify what it gives you.
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Nice to have:
- Experience with Ada, Intercom, Zendesk, or similar platforms.
- CI/CD, automated testing, and monitoring as part of delivery culture rather than bolted on.
- Background in hospitality or another operationally intensive SaaS vertical.
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