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Monte Carlo is an agent trust platform that unifies data and AI observability to monitor, troubleshoot, and improve production AI systems. As enterprises scale agent deployments across mission-critical use cases, Monte Carlo provides the reliability infrastructure needed for that transformation.
In this Senior Sales Engineer role, you will own technical sales cycles end-to-end for strategic US enterprise accounts. You'll drive discovery, solution design, demos, proof-of-value execution, and technical close independently while partnering with Account Executives on commercial strategy. Your focus will be helping customers understand how to observe, trust, and improve agent systems—from data pipelines feeding agents, to context retrieval, decision-making, and output production.
Key responsibilities include designing and executing proofs of value with agreed success criteria that convert to closed deals, building technical champions within accounts who advocate for Monte Carlo internally, and bringing a deep technical perspective to account planning and quarterly business reviews. You'll work with customers deploying agents on platforms like Databricks, Snowflake, and proprietary systems.
You bring 5+ years of pre-sales, solutions engineering, or strategic technical account management experience in B2B AI-first SaaS companies, with meaningful enterprise account exposure. You have hands-on experience with enterprise AI and agent deployments—either direct deployment experience or close collaboration with teams managing production agents. You're fluent in AI observability concepts (traces, spans, evaluations, instrumentation) and ideally have OpenTelemetry experience or exposure to enterprise AI platforms like Databricks Genie or Snowflake Cortex.
You balance technical and business acumen equally: comfortable whiteboarding agent architectures and discussing ROI and competitive positioning with VP-level stakeholders. You're self-directed, accountable, and a strong communicator across all seniority levels. Experience with the modern data stack (Snowflake, Databricks, dbt, Airflow, BigQuery), data observability, or enterprise account expansion is preferred but not required.
Success is measured by technical win rate on POVs, proper scoping and technical execution of pipeline opportunities, and revenue growth from closed commitments and consumption expansion.
About Monte Carlo Data
AI / Data / Infrastructure; Data & Analytics — data observability platform for data quality and reliability.
