Job Overview
Location
Remote, Americas
Job Type
Full-time
Category
Marketing
Date Posted
June 26, 2026
Full Job Description
đź“‹ Description
- • The AI Marketing Manager at Monte Carlo Data, Inc. is a builder who designs, ships, and owns AI-powered agents and automations that run the marketing function, operating like an engineer who ships production systems rather than PowerPoints.
- • Day to day, the role involves designing and shipping AI agents to replace high-volume manual marketing workflows (lead routing, contract handling, follow-up sequences, campaign execution), rebuilding marketing operations infrastructure with predictive lead scoring and lifecycle management, wiring together the marketing stack (Salesforce, HubSpot, Qualified, Clay, ZoomInfo, data warehouse), building personalization and testing tools, owning shipped systems through monitoring and iteration, and collaborating with marketing leadership, RevOps, and sales to identify high-leverage problems and translate them into working software.
- • Monte Carlo is the agent trust platform that unifies data and agent observability to monitor, troubleshoot, and improve production AI systems, empowering data and AI teams to ship trusted AI at scale, with a small, high-trust marketing team that moves fast and values output over process.
- • In this role, the person can learn to build production-grade AI agent systems end-to-end, gain deep expertise in integrating LLMs with enterprise marketing tools, develop systems thinking for reliable automation, and own impactful infrastructure that directly increases business efficiency without handoffs or committees.
🎯 Requirements
- • Built real systems on top of LLM APIs (Claude, OpenAI, or similar) — not just wrappers or chatbots, but agents wired into production workflows, with understanding of context management, tool use, prompt reliability, and when AI creates real leverage
- • Deep, hands-on familiarity with Salesforce, HubSpot, Qualified, Clay, and ZoomInfo, including knowledge of how data flows between these systems and what breaks when it doesn't
- • Technical fluency to build, deploy, and maintain AI agents and automation systems without engineering support, including ability to wire together LLM APIs, marketing tools, and workflows to create production systems that actually run
- • Systems thinking — treating built tools like products with fallback logic, monitoring, iteration loops, and knowing when to rebuild vs. patch
- • Stakeholder judgment — ability to work across marketing, RevOps, and sales, absorb messy requirements, and turn them into clean, scoped builds while pushing back on scope creep that threatens quality
🏖️ Benefits
- • End-to-end ownership: problem identification, build, deployment, iteration — no handoffs, no committees
- • Competitive compensation, equity, and a remote-first environment
- • Small, high-trust marketing team that moves fast and values output over process
- • Opportunity to build AI-powered infrastructure that most companies are still theorizing about, backed by Monte Carlo's data platform
- • Recognition as a top workplace: Named 2026 Best Place to Work by Built In, #1 Data Observability Platform by G2 for 4th consecutive quarter, and 2025 Databricks Data Governance Partner of the Year
Skills & Technologies
See exactly how your profile matches this role — strengths, skill gaps, and what to do about them.
About Monte Carlo Data, Inc.
Monte Carlo Data, Inc. provides a data observability platform that monitors data pipelines, detects anomalies, and alerts teams to data quality issues across warehouses, lakes, and ETL systems. It automates lineage tracking, impact analysis, and root-cause investigation to reduce downtime and improve trust in analytics and machine-learning outputs. The company serves data engineers, analysts, and data scientists in finance, e-commerce, healthcare, and technology sectors, integrating with Snowflake, Databricks, BigQuery, Redshift, and Airflow to deliver real-time reliability metrics and governance controls.
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