GTM Systems Architect

Fyxer

About The Position

Fyxer is an AI company that has grown from $1M to $35M ARR in a year. We have a product that works, a team delivering results, and a PLG motion converting prosumer users into enterprise contracts. What we’re building next is the intelligence layer on top — the systems, signals and automation that turn a fast-growing company into a precision revenue machine. This role exists to build that layer. Not by owning the day-to-day tools we have people for that — but by sitting above the operational layer and asking: what should be automated? What signals are we not acting on? Where can AI move a revenue metric faster than a human can? The best GTM teams design their revenue architecture around outcomes, not activities. That’s the standard we’re building to — and we need someone who can go and make it happen.

Requirements

Able to code — scripting automations, working with APIs, standing up lightweight tools without needing engineering support
Familiar with AI workflow tooling — Clay, Gong integrations, Dust, or similar
Understands CRM architecture well enough to know what good looks like, even if day-to-day HubSpot ownership sits elsewhere
Comfortable working with data teams: knows what signals to ask for and how to act on them
8+ years in a relevant role — RevOps, GTM operations, or data engineering with a commercial focus
Has operated at the intersection of revenue operations and tooling in a scaling B2B SaaS company
Commercial and technical in equal measure - you bridge the gap between what the commercial team needs and what’s worth building technically.
You’re curious, you think like a detective, and you connect data signals to revenue outcomes.
Builder, not just configurer - You’ve done this work the hard way — before AI existed — and you now use AI to do it ten times faster.
You know what’s worth building and what’s just noise.
You apply AI thoughtfully, not experimentally.
Every workflow you build, you’re asking: does this actually help someone close a deal or retain a customer?

Nice To Haves

Backgrounds worth considering beyond traditional RevOps: ex-consultants, systems engineers, operators who’ve built from scratch
The archetypal profile: someone who has owned the GTM data and automation layer at a high-growth, product-led SaaS company — think Ramp, Rippling, Notion, or Vercel — where you’ve seen what great looks like and built it yourself. If you’ve done this somewhere less well-known but with the same rigour, that’s equally valid

Responsibilities

Build the automated signal layer — churn risk, expansion triggers, pipeline health — so Sales and CS have the intelligence they need without asking for it
Design out the most painful manual work across the revenue team, not delegate it
Have at least one AI-powered workflow live and demonstrably moving a revenue metric
Work autonomously — setting the agenda, not waiting for one
Identify and eliminate manual work that shouldn’t exist.
Build AI-powered workflows across the full sales and CS motion — from prospecting through to renewal and expansion.
Automate the prep, the follow-up, the note-taking.
Free the team up to sell and retain.
Build systems that make the revenue team measurably more effective: automated briefings, proactive churn and expansion signals, real-time coaching.
Reduce the time it takes to prepare for, run and follow up from every customer interaction.
Take a view on the full GTM tech stack.
Bring the strategic direction and prioritisation that turns a list of tools into a coherent system.

Benefits

Autonomy: We hire people who want ownership and then we actually give it to them.
Velocity: You will be fast-tracked into senior responsibilities far earlier than at a traditional company.
Scale: We are on track to hit $100M in revenue by the end of 2026. This is a rare opportunity to join a high-growth rocket ship at the foundational stage.

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