Monte Carlo

HQ
San Francisco
Total Offices: 8
135 Total Employees
50 Product + Tech Employees
Year Founded: 2019
All Teams

Monte Carlo Customer Success Team

What People Are Saying About Monte Carlo

  • Mission & Purpose: Work is explicitly tied to “Customer Impact,” with onboarding centered on product, personas, and hands-on demos plus a “Week 1 Ship” ritual that links CS efforts to reducing data downtime and enabling trusted AI. CS is framed as core to time-to-value and outcomes across the customer lifecycle.
  • Team Support: CS acts as the “connective tissue” with Product, Solutions/SEs, Support, and Engineering, co-running enablement like Mastery sessions that turn field insights into best practices. Colleagues are described as collaborative and supportive in a remote-first setup with regular AMAs, weekly syncs, and offsites that keep execution tight.
  • Learning & Development: Structured onboarding and ongoing enablement—mentorship, Lunch & Learns, certifications, and CS-led education on alert fatigue and monitoring strategy—signal investment in practitioner craft. New hires ramp on technical domains and customer personas so CS can teach and codify best practices.

Recently posted jobs

6 Days AgoSaved
In-Office or Remote
London, Greater London, England, GBR
Big Data • Cloud • Software • Generative AI • Big Data Analytics
Drive new-logo sales across Global 2000 accounts by developing consultative sales strategies, generating pipeline, leading discovery and business value assessments, presenting to executive buyers, and closing complex software cloud deals. The role partners with sales engineering, marketing, partnerships, and customers while selling technical products to data and engineering teams. It is ideally hybrid in London one to two days weekly.
One Month AgoSaved
Remote
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Big Data • Cloud • Software • Generative AI • Big Data Analytics
Build production AI agents and agent-powered features from research and prototyping through deployment. Develop evaluation infrastructure with golden datasets, regression suites, and offline/online scoring. Own retrieval and context pipelines, production instrumentation, failure taxonomies, and cost and latency budgets. Partner with data science and product management on experiments and agent behavior, while establishing LLM engineering patterns, guardrails, and reusable tooling.
One Month AgoSaved
In-Office or Remote
4 Locations
Big Data • Cloud • Software • Generative AI • Big Data Analytics
Qualify inbound leads and outbound to strategic prospects, triage against ICP, build the inbound playbook with marketing, use AI tools to research and personalize outreach, prioritize pipeline, and convert high-quality prospects into opportunities.