---
title: 'AI Marketing Operations Manager (GTM Engineer) at Monte Carlo'
canonical: 'https://feeny.ai/job/ai-marketing-operations-manager-gtm-engineer-monte-carlo-americas-2h95v3r7dm3k'
type: 'job'
last_seen: '2026-09-15'
---

# AI Marketing Operations Manager (GTM Engineer) at Monte Carlo

- **Company:** Monte Carlo
- **Location:** Americas
- **Employment:** full-time
- **Work type:** remote
- **Posted:** 2026-06-24
- **Last confirmed live:** 2026-09-15
- **Apply:** https://jobs.ashbyhq.com/montecarlodata/b712825a-43b1-4fc8-a831-b58c01db0aa3

## Job description

## About Monte Carlo

Monte Carlo is the agent trust platform that unifies data and agent observability to monitor, troubleshoot, and improve production AI systems. As enterprises prepare to deploy thousands of agents across business-critical use cases, Monte Carlo provides the reliability infrastructure to support them along this AI transformation, from human-guided agents to fully autonomous operations. Founded in 2019 and backed by leading investors, Monte Carlo empowers data and AI teams to ship trusted AI at scale. Learn more at [montecarlodata.com](http://montecarlodata.com).

## 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 (GTM Engineer) 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.

## #LI-REMOTE

## #BI-REMOTE

Come As You Are Equality is a core tenet of Monte Carlo's culture. We are committed to building an inclusive global team that represents a variety of backgrounds, perspectives, beliefs, and experiences.

Monte Carlo is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

We are proud to be recognized for our world-class employee experience: [Monte Carlo Named 2025 Databricks Data Governance Partner of the Year](https://www.montecarlodata.com/blog-2025-databricks-data-governance-partner-of-the-year/?utm_source=chatgpt.com) [We were recently recognized as the #1 Data Observability Platform by G2 for the 4th consecutive quarter. See our G2 reviews here!](https://www.g2.com/reports/grid-report-for-data-observability-spring-2025.embed?featured=monte-carlo&secure%5Bgated_consumer%5D=7d02ec0a-326a-40fa-8a44-fab49f67c5f1&secure%5Btoken%5D=6b3c29d18ea50ae0005295b5c63994f97c01cae81bbd3f9ea6abff73c40fde51&utm_campaign=gate-2063400) [Monte Carlo Named to G2's Best Software Products of 2026](https://www.montecarlodata.com/blog-monte-carlo-g2-best-software-product-of-2026/) https://www.dbta.com/Editorial/Trends-and-Applications/Trend-Setting-Products-in-Data-and-Information-Management-for-2025-167115.aspx [We are super proud to be named the 2026 Best Place to Work by Built In!](https://builtin.com/awards/us/2026/best-places-to-work) Beware of Imposter Recruiters and Job Scams

- All official communication from our recruiting team will come from an @[montecarlodata.com](http://montecarlodata.com) email address.
- We will never ask candidates to provide sensitive personal information (such as bank details, social security numbers, or payment) at any stage of the recruitment process.
- We will never request payment for equipment, training, or application processing.
- Our open positions are always listed on our official careers page: https://jobs.ashbyhq.com/montecarlodata.

If you are contacted by someone claiming to represent Monte Carlo but you’re unsure of their legitimacy, please reach out to us directly at recruiting@montecarlodata.com before sharing any personal information.

## About Monte Carlo

## Company Overview
- **One-liner**: Monte Carlo provides an autonomous observability platform that unifies data and agent observability to monitor, troubleshoot, and improve production AI systems.
- **Entity Type**: Private (Series D, $135M raised May 2022)
- **Headquarters**: San Francisco, California, United States
- **Founded**: 2019
- **Founders**: Not publicly listed as founders in provided sources (likely Lior Gavish as CTO and others; not explicitly named)

## Core Business
- **Primary industries**: Data infrastructure, AI observability, Software Development
- **Target customers**: Enterprise B2B – data and AI teams at large organizations (400+ enterprise customers including JetBlue, Roche)
- **Mission / purpose**: "Reduce data downtime" and enable enterprises to ship trusted AI at scale by providing reliability infrastructure for agents and data pipelines.

## Products & Services
- **Monte Carlo Platform**: An end-to-end autonomous observability platform that monitors data pipelines, agents, and AI systems in production. Includes features like anomaly detection, data lineage, and incident resolution. Type: SaaS.
- **Agent Trust Platform**: A newer capability focused on monitoring and troubleshooting AI agents in production, unifying data observability with agent observability.

## Market Standing
- **Valuation / Market Cap**: Not disclosed (private); total funding $236M (Seed, Series A $16M, Series B $25M, Series C $60M, Series D $135M)
- **Key Metric**: Total Funding $236M; Annual Revenue reported as $2M (likely placeholder/outdated – LinkedIn often shows symbolic revenue). 400+ enterprise customers, 10M tables monitored, 1,000 incidents resolved daily.
- **Notable Investors/Partners**: Accel (lead in Seed & Series A), Redpoint, Notable Capital (Series B), ICONIQ Growth (Series C), IVP (Series D). Partners include Alation, Sigma, Fivetran, Snowflake, Databricks.
- **Growth Signals**: +9.8% YoY headcount growth (212 employees), operates in 14 countries, recent launch of "Trusted Data for AI (TDAI) Advisory Council" (Aug 2024), support for Apache Kafka and vector databases (Nov 2023). Recognized by Forrester with a TEI study showing 375% ROI and $1.5M avoided losses.

## Competitive Advantages
- First-to-market autonomous observability platform combining data and agent monitoring.
- Deep integrations with modern data stacks (Snowflake, Databricks, dbt, Fivetran, Kafka) and AI frameworks.
- Strong enterprise adoption (JetBlue, Roche) and validated ROI (Forrester study).
- 80% reduction in data downtime reported by customers.

## Strategic Focus
- Expanding from data observability to "agent trust" to support the explosion of AI agents in production.
- Building out the "Monte Carlo for AI" go-to-market, with a dedicated Advisory Council.
- Scaling global presence (14 countries) and deepening partnerships with major cloud and data platforms.

## Why Work Here
- **Culture**: Values include "Measure in minutes" (urgency), "Ship and iterate" (high expectations with iteration), "Customer impact", and "Beat the odds" (ambition, learning from failure). Emphasizes a positive, team-oriented environment.
- **Work policy**: Not explicitly stated as fully remote, but based on LinkedIn locations (HQ in San Francisco, offices in multiple US cities, and distributed teams across 14 countries) it likely supports hybrid/remote. The careers page mentions "Global Office and Culture Manager".
- **Engineering culture**: High degree of execution and collaboration; tech stack includes Python, TypeScript, React, GraphQL, Snowflake, Databricks, and modern observability tools (DataDog, PagerDuty). Employees come from top tech companies (Google, Snowflake, Twilio, Confluent).
- **Perks**: Not detailed in public sources, but the "Have fun" value and focus on authenticity suggest a strong culture. Recent departures of some senior sales and marketing leaders may indicate restructuring.
- **Candidate note**: Official communication only from @montecarlo.ai emails; beware of scams.

## Sources
1. [montecarlo.ai - About Us](https://montecarlo.ai/about-us)
2. [montecarlo.ai - Homepage](https://montecarlo.ai/)
3. [Monte Carlo Careers](https://www.montecarlodata.com/careers-at-monte-carlo/)
4. [LinkedIn Company Profile](https://www.linkedin.com/company/monte-carlo-data)

## Other roles at Monte Carlo

- [Applied AI Engineer](https://feeny.ai/job/applied-ai-engineer-monte-carlo-americas-385312hg9b1q) — Americas
- [Strategic Sales Development Representative](https://feeny.ai/job/strategic-sales-development-representative-monte-carlo-americas-fghbgsxwt9qz) — Americas
- [Partner Manager, EMEA](https://feeny.ai/job/partner-manager-emea-monte-carlo-london-t76b7v5jfbjn) — London, United Kingdom