---
title: 'Sr. Sales Engineer (Forward Deployed Engineer - Pre Sales) at Monte Carlo'
canonical: 'https://feeny.ai/job/sr-sales-engineer-forward-deployed-engineer-pre-sales-monte-carlo-americas-8h9wt7p774ex'
type: 'job'
last_seen: '2026-10-13'
---

# Sr. Sales Engineer (Forward Deployed Engineer - Pre Sales) at Monte Carlo

- **Company:** Monte Carlo
- **Location:** Americas
- **Compensation:** $240k–$270k
- **Employment:** full-time
- **Work type:** remote
- **Posted:** 2026-09-29
- **Last confirmed live:** 2026-10-13
- **Apply:** https://jobs.ashbyhq.com/montecarlodata/fb989422-381a-4049-8093-38cd1a36ff77

## 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 [montecarlo.ai](https://montecarlo.ai)

The Opportunity The largest US enterprises are deploying agents into production right now — and discovering that trust, reliability, and observability are the difference between a pilot and a platform. We're looking for a sales engineer who has lived that reality and can help our strategic customers navigate it. You'll own the technical win inside strategic US accounts, partnered directly with Account Executives, and working fully remote.

## What You'll Do

- Run technical sales cycles end to end. Own discovery, solution design, demos, POV execution, and technical close for opportunities within strategic US enterprises. Partner with Account Executives on commercial strategy; drive the technical win independently.
- Sell into the agentic stack. Our customers are deploying agents on Databricks, Snowflake, and their own platforms. You'll help them understand how to observe, trust, and improve those systems — from the data pipelines feeding agents, to the context they retrieve, the decisions they make, and the outputs they produce.
- Drive POVs that convert. Design proofs of value with agreed success criteria, manage the evaluation, and deliver results that remove technical objections and accelerate the commercial close.
- Build technical champions. Identify and develop the advocates inside each account who will carry Monte Carlo into the next budget cycle, platform decision, or executive review. Run briefings, workshops, and architecture reviews that position our platform as infrastructure.
- Bring a technical point of view. Understand each customer's data and AI architecture deeply — where agents run, how they're instrumented, and where reliability breaks down. Bring that perspective to every account plan and QBR.

## What We're Looking For

- Hands-on experience with enterprise AI and agent deployments. You've deployed agents in enterprise organizations — or worked closely enough with teams that do to understand the architecture, the failure modes, and the operational reality. You know what it takes to get an agent from demo to production.
- Fluency in AI observability concepts. Traces, spans, evaluations, instrumentation — these are working vocabulary, not buzzwords. Experience with OpenTelemetry is highly prized, as is exposure to Databricks Genie, Snowflake Cortex, or similar enterprise AI platforms.
- 3+ years in pre-sales, solutions engineering, or strategic technical account management within B2B AI-first companies and SaaS organizations, with meaningful experience in enterprise accounts. You've navigated procurement, infosec reviews, and multi-stakeholder buying committees.
- Domain background in data, observability, agent trust, or agent-first products. You've worked in one of these, not next to one.
- Equal parts technical and business focused. You can whiteboard an agent architecture and hold a conversation with a VP of Data & AI about ROI and competitive positioning. Credible with engineers, effective with executives.
- Self-directed and accountable. A lean team with high-value accounts. You prioritize your own time, know when to escalate, and know when to push back.
- Strong communicator across seniority levels. Equally comfortable in a technical deep-dive with a platform engineer and presenting a business case to a C-minus-1.

## Preferred, Not Required

- Modern data stack experience: Snowflake, Databricks, dbt, Airflow, BigQuery, or similar. Data observability or data quality experience is a plus.
- Experience growing existing enterprise accounts — expansion, upsell, or land-and-expand motions.
- Familiarity with MEDDPICC, Command of the Message, or similar sales qualification and value frameworks.
- Experience selling into enterprises across multiple countries and regulatory environments.
- Hands-on prototyping during a sales cycle.

## How We'll Measure Success

- Technical win rate on POVs. The POVs you run should convert. You set agreed success criteria upfront and deliver against them.
- Technical execution against pipeline. Every opportunity properly scoped, proven, and technically closed.
- Revenue growth. Closed commitments should translate into growing consumption over time, and your technical work sets that trajectory.

This Is Not For You If

- Your background is post-sales or implementation only, without having carried a technical win inside a live deal
- You get handed qualified opportunities and run the demo, rather than owning discovery yourself
- You can't describe a real agent deployment — its architecture, how it was instrumented, or how it failed
- Your enterprise experience stops at mid-market, without procurement, infosec review, or multi-stakeholder buying committees

## #LI-REMOTE

## #BI-REMOTE

## Why Monte Carlo

- We created the data observability category, and we're doing it again with [agent trust](https://montecarlo.ai/agent-trust) — you'll build where the market is forming, not where it's settled
- Series D, $236M raised, backed by Accel, Redpoint, Notable Capital, ICONIQ Growth, and Salesforce Ventures
- Customers include HubSpot, Fox, Nasdaq, Toast, and Mercado Libre — your work ships to enterprises with real stakes
- Snowflake Partner of the Year and a verified connector in Anthropic's Claude AI directory
- Remote-first by design since day one, and recognized as a Best Workplace for it
- Competitive compensation, equity, and a remote-first environment.

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

- [Strategic Account Executive, AMER](https://feeny.ai/job/strategic-account-executive-amer-monte-carlo-united-states-c5k0dazz9s4h) — United States
- [Senior Backend Engineer](https://feeny.ai/job/senior-backend-engineer-monte-carlo-united-states-mnmxvcd5sns7) — United States
- [Strategic Account Executive, London](https://feeny.ai/job/strategic-account-executive-london-monte-carlo-london-a6262ksgc01z) — London, United Kingdom
- [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