Monte Carlo

Applied Forward Deployed Engineer

Remote, Americas · Vp

Sponsorship not specifiedDetected 72 days ago

PythonSQLSnowflakeDatabricksRESTAirflowdbtData ScienceData VisualizationIncident ResponseCustomer Success

About the role

An Applied Forward Deployed Engineer, someone who takes ownership the moment a deal closes and doesn't let go until the customer is fully live, deeply adopted, and driving real value from Monte Carlo.
This is a post-sale role inside our GTM organization, focused entirely on deployment, adoption, and getting customers to consumption.
You'll work closely with Customer Success and Account teams, but your metric is technical - is this customer live, and are they getting value?

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.

You can run a room of data engineers and give a crisp status update to a VP in the same week without switching personas.

Familiarity with the tools that surround the warehouse - dbt, Airflow, Fivetran, Looker, or similar - is a strong plus.

Own onboarding and deployment from day one post-close - getting customers live on Snowflake, Databricks, and adjacent stack components with the right monitors, alerts, and integrations configured for their environment.
Drive customers to consumption - you're accountable for ensuring they're actively using what they bought and realizing measurable value, not just technically deployed.
Unblock customers fast - diagnosing deployment issues, resolving edge cases, and removing whatever stands between a signed contract and a fully operational Monte Carlo environment.
Build adoption depth beyond the initial champion - helping customers expand usage across teams, data assets, and use cases to drive long-term stickiness.
Become the technical advisor customers call before they escalate - shaping how they operationalize data observability and growing into a trusted extension of their data team.
Feed deployment and adoption signals back to Product and Engineering - you'll have the clearest view of what's working in production and where customers get stuck.
Monte Carlo is the agent trust platform that unifies data and agent observability to monitor, troubleshoot, and improve production AI systems.
Founded in 2019 and backed by leading investors, Monte Carlo empowers data and AI teams to ship trusted AI at scale.

This listing is sourced directly from Monte Carlo's careers page and normalized into a canonical job model.