Applied Forward Deployed Engineer
Monte Carlo Data
Applied Forward Deployed 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.
We're hiring an Applied Forward Deployed Engineer (Post-Sales) to own the technical side of every new customer from the moment the deal closes until they're live and getting value. You'll write production code in customers' Snowflake and Databricks environments, integrate Monte Carlo with their real pipelines, and become the technical advisor they call before they escalate. This isn't support and it isn't a CSM role: your metric is whether the customer is live and consuming. It's an early hire into a new function, so you'll help write the FDE playbook, not inherit one. Remote (US), with roughly 25% travel to customers.
Own deployment from day one post-close: monitors, alerts, and integrations configured for the customer's actual environment.
Write production-quality Python, SQL, and API integrations tailored to customer pipelines, and clear whatever stands between a signed contract and a fully operational deployment.
Drive customers to consumption. You're accountable for active usage and measurable value, not just go-live.
Expand adoption beyond the first champion across teams, data assets, and use cases.
Feed what you see in the field back to Product and Engineering so it shapes the core product instead of turning into one-off work.
Shape the FDE playbook as an early member of the team.
Data platform depth. 5+ years building on Snowflake, Databricks, or a modern cloud warehouse as the person who designed and built it, not an end user. Production Python and SQL, and comfortable wiring up REST APIs in someone else's environment.
Post-sale ownership. You've owned technical outcomes for enterprise customers after the contract: implementation, solutions or forward deployed engineering, technical onboarding. You measure yourself on go-live and adoption.
Range with people. You can run a working session with a room of data engineers and brief a VP in the same week.
Builder in ambiguity. You've operated without a playbook and built the structure yourself. You create motion instead of waiting for direction.
Nice to have. dbt, Airflow, Fivetran, or Looker; data quality, pipeline monitoring, or incident response; a background in data observability or an adjacent category.
You want a support queue or a defined playbook to follow.
You've only worked pre-sale and never owned what happens after the contract is signed.
Your data experience is all internal, with no customer-facing context.
You'd rather advise on the stack than write code in it.
#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