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 montecarlodata.com.
The opportunity
The largest enterprises in the US 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.
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 organisations — 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.
5+ years in pre-sales, solutions engineering, or strategic technical account management within B2B AI-first companies and SaaS organisations — with meaningful experience in enterprise accounts. You’ve navigated procurement, infosec reviews, and multi-stakeholder buying committees.
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 US team with high-value accounts. You prioritise 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
Experience with the modern data stack: 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 US enterprises across multiple states and regulatory environments.
How we’ll measure success
Technical win rate on POVs. 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. Still important — closed commitments should translate into growing consumption over time, and your technical work sets that trajectory.
Compensation
70⁄30 base-to-variable split. Variable is weighted toward commit attainment — helping close opportunities is the priority — with a revenue growth component recognising the compounding impact of your technical work. You earn more when you help close.
#LI-REMOTE
#BI-REMOTE
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
We were recently recognized as the #1 Data Observability Platform by G2 for the 4th consecutive quarter. See our G2 reviews here!
Monte Carlo Named to G2’s Best Software Products of 2026
Monte Carlo was featured on Database Trends and Applications (DBTA’s) Trend-Setting Products for 2025!
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.
