Full-Time

AI Marketing Operations Manager

Monte Carlo Data

Monte Carlo Data

501-1,000 employees

End-to-end data observability and incident resolution

No salary listed

Remote in USA

Remote

Remote within the Americas.

Category
Growth & Marketing (1)
Required Skills
LLM
Claude
OpenAI
HubSpot
Salesforce
Observability

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Requirements
  • You have built real production systems on top of large language model application programming interfaces such as Claude, OpenAI, or similar, including agents wired into production workflows.
  • You understand context management, tool use, prompt reliability, and when artificial intelligence creates real leverage versus when it adds noise.
  • You have deep, hands-on familiarity with Salesforce, HubSpot, Qualified, Clay, and ZoomInfo, including how data flows between these systems and what breaks when it does not.
  • You can build, deploy, and maintain artificial intelligence agents and automation systems without engineering support.
  • You can wire together large language model application programming interfaces, marketing tools, and workflows to create production systems that run.
  • You understand fallback logic, monitoring, iteration loops, and when to rebuild versus patch.
  • You can work across marketing, revenue operations, and sales, absorb messy requirements, and turn them into clean, scoped builds.
  • You have shipped something with a large language model application programming interface beyond a side project.
  • You are self-directed and able to own systems end-to-end.
Responsibilities
  • Design and ship artificial intelligence agents that replace high-volume manual marketing workflows, including 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 Salesforce, HubSpot, Qualified, Clay, ZoomInfo, and the 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 by monitoring them, building fallback logic, instrumenting them for observability, and iterating on results.
  • Work directly with marketing leadership, revenue operations, and sales to identify high-leverage problems and translate them into working software.
  • Identify problems, build solutions, deploy them, and iterate without handoffs.
Desired Qualifications
  • Coding experience is a plus.

Monte Carlo Data provides end-to-end data observability to improve data reliability. Its platform continuously monitors real-time data status, including freshness, volume, schema, and quality, so data engineers can verify data integrity. It includes incident detection and resolution tools that alert, investigate, and prevent data issues at scale, and it integrates with Slack, Teams, and JIRA to fit existing workflows. The company aims to help data-dependent organizations avoid bad data by enabling reliable, transparent, and scalable data operations.

Company Size

501-1,000

Company Stage

Series D

Total Funding

$236M

Headquarters

San Francisco, California

Founded

2019

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Simplify Jobs

Simplify's Take

What believers are saying

  • Axios used Monte Carlo in July 2026 for AI tagging across 12 LLM applications.
  • Monte Carlo's March 2026 workforce reduction cut burn while preserving the platform.
  • The June 2026 Snowflake and Databricks wins expand distribution inside two anchor ecosystems.

What critics are saying

  • March 26, 2026 layoffs hit 30% of staff, signaling pressure on growth.
  • Datadog, Bigeye, Anomalo, and open-source alternatives compress pricing across data observability.
  • If Snowflake or Databricks bundle observability natively, Monte Carlo becomes a feature.

What makes Monte Carlo Data unique

  • Monte Carlo's June 15, 2026 Databricks Agent Bricks integration spans data and agent layers.
  • July 2026 Agent Observability tracks context, performance, behavior, and outputs in one product.
  • June 2, 2026 Snowflake named Monte Carlo 2026 Data Governance Product Partner of the Year.

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Benefits

Remote Work Options

Growth & Insights and Company News

Headcount

6 month growth

2%

1 year growth

3%

2 year growth

-2%
DPEX Network
Jun 2nd, 2026
Monte Carlo named 2026 Data Governance Snowflake Product Partner of the Year.

Monte Carlo named 2026 Data Governance Snowflake Product Partner of the Year. Recognition highlights Monte Carlo's data & AI observability leadership and commitment to helping enterprises run reliable AI on Snowflake SAN FRANCISCO, June 02, 2026 (GLOBE NEWSWIRE) - Monte Carlo today announced at Snowflake's annual user conference, Snowflake Summit 2026, that it has been named the 2026 Data Governance Snowflake Product Partner of the Year by Snowflake, the AI Data Cloud company. Monte Carlo was recognized for its achievements as part of the Snowflake AI Data Cloud, helping joint customers achieve the end-to-end visibility they need to run reliable AI on Snowflake, from the data powering agents, to the behavior, performance, and outputs of those agents. Together, Monte Carlo and Snowflake are empowering teams to deploy trusted AI at scale. "Agentic AI is transforming how enterprises operate - but that transformation only works if both the agents and their underly... Third-Party Content Disclaimer Content displayed on this platform may include news articles, reports, and other materials aggregated from publicly available third-party sources through automated tools. Such content is not created, written, commissioned, or edited by Straits Interactive Pte Ltd or the Data Protection Excellence (DPEX) Network. While DPEX Network take reasonable steps to ensure responsible publication, DPEX Network do not independently verify all third-party information and make no representations as to its accuracy, completeness, or reliability. The views, findings, and statements expressed in third-party content belong solely to the original source and do not reflect the views of Straits Interactive Pte Ltd or the DPEX Network. If you believe any content is inaccurate, infringing, or should be removed, please contact DPEX Network at [email protected]. DPEX Network will review the matter and, where appropriate, take action in accordance with its internal policies.

Yahoo Finance
Mar 12th, 2026
Monte Carlo launches Agent Observability as 73% of enterprises demand monitoring before AI deployment

Monte Carlo has launched Agent Observability capabilities providing unified visibility across AI agent lifecycles. The platform monitors four critical pillars: context, performance, behaviour and outputs, addressing a significant gap in enterprise AI deployment. A Monte Carlo survey reveals 73% of enterprises require monitoring and alerting before deploying AI agents, yet 63.4% cite lack of observability as a top deployment barrier. Additionally, 53% of enterprises expect to significantly rebuild or redesign already-deployed AI agent systems. The platform enables teams to detect hallucinations, diagnose performance issues and validate workflow execution. Axios is using Monte Carlo to ensure accuracy in its AI-powered content tagging system, initially built with OpenAI, with plans to expand across 12 additional large language model applications.

Built In SF
Feb 23rd, 2026
G2 Recognizes Monte Carlo in 2026 Best Software Awards

G2 recognizes Monte Carlo in 2026 Best Software Awards. The company's data and AI observability platform leverages automation capabilities to efficiently combat data downtime and help enterprises ensure reliability and performance across their systems. Published on Feb. 23, 2026 Rose Velazquez | Feb 23, 2026 Monte Carlo was recently featured in G2's Best Software Awards for 2026, with recognition among the top 50 products for IT infrastructure and IT management. The data and AI observability company earned its placement based on verified user reviews and ratings. The annual ranking identifies top-tier software companies across various categories, emphasizing user satisfaction and product impact. The company's platform is designed to help organizations maintain the health and quality of their data and AI systems. By using machine learning to monitor data pipelines, the technology identifies and alerts teams to data downtime, which refers to periods when data is missing, inaccurate or otherwise broken. This automated approach allows engineers to resolve issues before they affect business operations or decision-making processes. According to Monte Carlo, recent G2 reviews highlight its product's proactive issue detection, time and resource savings for engineering teams, straightforward implementation and immediate value. "We love seeing proof of our mission out in the wild everyday, and are confident that Monte Carlo is helping engineers and data leaders reduce risk, save time and trust their data more than ever before," the company's announcement stated. This article was drafted by a generative AI tool, using information from press releases and company blogs provided by our staff. All content was reviewed by a Built In editor and went through a fact-checking process to ensure accuracy. Errors can be reported to our team at [email protected].

TechTarget
Apr 17th, 2025
Monte Carlo launches first agents for data observability

Monte Carlo has entered the agentic AI era, launching Observability Agents on Thursday to help enterprises ensure data quality.

Business Wire
Nov 14th, 2024
Monte Carlo Announces New GenAI Capabilities to Streamline Data Quality Management at Enterprise Scale

Additionally, to help these and other data and AI reliability initiatives scale and operationalize more effectively, Monte Carlo introduced the Data Operations Dashboard, which gives insights into key operational metrics like number of incidents by data asset owner, time to detection and time to resolution.