AI Marketing Operations Manager

The Role
Marketing teams are drowning in manual workflows while AI tools proliferate — and almost no one is building the actual infrastructure to connect them. Monte Carlo is hiring an AI Marketing Operations Manager to change that: a builder who designs, ships, and owns AI-powered agents and automations that run our marketing function. This role sits inside Marketing but operates like an engineer — you ship production systems, not PowerPoints.

What You'll Do
Design and ship AI agents that replace high-volume manual marketing workflows — lead routing, contract handling, follow-up sequences, and campaign execution

Rebuild marketing operations infrastructure with predictive lead scoring, lifecycle management, and agent-forward workflows that increase business efficiency

Wire together the marketing stack — Salesforce, HubSpot, Qualified, Clay, ZoomInfo, and our data warehouse — so the right data reaches the right system at the right time

Build personalization and testing tools that improve campaign performance at scale

Own the systems you ship: monitor them, build fallback logic, instrument for observability, iterate on results

Work directly with marketing leadership, RevOps, and sales to identify the highest-leverage problems and translate them into working software

What We're Looking For

LLM Engineering — You've built real systems on top of LLM APIs (Claude, OpenAI, or similar) — not just wrappers or chatbots, but agents wired into production workflows. You understand context management, tool use, prompt reliability, and when AI creates real leverage vs. when it adds noise.

B2B Marketing Stack — You have deep, hands-on familiarity with Salesforce, HubSpot, Qualified, Clay, and ZoomInfo. You know how data flows between these systems and what breaks when it doesn't.

Technical Fluency — You can build, deploy, and maintain AI agents and automation systems without engineering support. You know how to wire together LLM APIs, marketing tools, and workflows to create production systems that actually run. Coding experience is a plus, but it's not required — what matters is that you're technical enough to own these systems end-to-end.

Systems Thinking — You treat the tools you build like products. That means fallback logic, monitoring, iteration loops, and knowing when to rebuild vs. patch.

Stakeholder Judgment — You can work across marketing, RevOps, and sales, absorb messy requirements, and turn them into clean, scoped builds. You push back when scope creep threatens quality.

This Is Not For You If
You want to recommend AI tools, not build them

You expect engineering to own deployment and maintenance after you design

You need a lot of structure and hand-holding — this role is self-directed from day one

You haven't shipped anything with an LLM API beyond a side project

You're looking for a traditional marketing ops or marketing analytics role

Why Monte Carlo
Monte Carlo's marketing team has the mandate to build AI-powered infrastructure that most companies are still theorizing about — and the data platform to back it up

You'll have end-to-end ownership: problem identification, build, deployment, iteration — no handoffs, no committees

The company is the data observability category leader and actively expanding into AI agent reliability — this role sits at that intersection

Small, high-trust marketing team that moves fast and values output over process

Competitive compensation, equity, and a remote-first environment.