Senior Sales Engineer
Monte Carlo Data
Senior Sales Engineer
Monte Carlo Data
End-to-end data observability and incident resolution
About Monte Carlo
Monte Carlo is the agent trust platform that autonomously observes, fixes, and continuously improves agents and the data that powers them — so enterprises can scale trust at the speed of AI. Bayes, our AI teammate, does the work: detecting, triaging, troubleshooting, and fixing issues in AI agents and the data powering them. The result is self-improving agents that get better with every fix instead of drifting. More than 400 enterprises, including Amazon, PepsiCo, CNN, Nasdaq, and JetBlue, rely on Monte Carlo. Learn more at montecarlo.ai.
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.
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.
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.
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.
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.
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
We created the data observability category, and we're doing it again with 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
Monte Carlo Named to G2's Best Software Products of 2026
We are super proud to be named the 2026 Best Place to Work by Built In!
Beware of Imposter Recruiters and Job Scams
All official communication from our recruiting team will come from an @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 [email protected] before sharing any personal information.
End-to-end data observability and incident resolution
Monte Carlo Data provides end-to-end data observability and AI-powered data reliability for real-time monitoring of data quality, freshness, volume, and schema to help data engineers ensure data integrity. Its platform continuously observes data pipelines and datasets, surfaces issues through alerts and dashboards, and includes incident detection and resolution that trigger workflows in tools like Slack, Teams, and JIRA. The service differentiates itself by focusing specifically on data reliability and end-to-end observability with built-in incident management and cross-tool integrations, rather than generic monitoring. The goal is to prevent bad data from affecting business decisions by enabling reliable, transparent, and scalable data operations that teams can trust.
Explore more opportunities at Monte Carlo Data