Full-Time
End-to-end data observability and incident resolution
No salary listed
Remote in USA
Remote
Remote within the Americas.
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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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Remote Work Options
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.
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.
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].
Monte Carlo has entered the agentic AI era, launching Observability Agents on Thursday to help enterprises ensure data quality.
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.