Applied Forward Deployed Engineer (FDE)

About the role

This is a field engineering role for someone who can sit across from a customer, understand what they're trying to build, and go write it. You'll prototype integrations and connectors based on real customer requests, conduct rapid field testing in live environments, and relay what you learn back to Engineering so the best solutions make it into the core product. You're the link between what customers need today and what Monte Carlo ships tomorrow.

What You'll Do

• Meet with customers to understand their technical requirements, data environments, and integration gaps — then translate those conversations into working prototypes
• Build integrations and connectors tailored to customer data stacks (Snowflake, Databricks, Salesforce, and others) using Python, SQL, and REST APIs
• Run rapid field testing in customer environments — ship fast, validate fast, iterate fast
• Document what you learn and relay it back to Engineering: what customers are asking for, what worked, what didn't, and why
• Work alongside senior FDEs to hand off proven solutions that can scale into the core product
• Become a trusted technical contact for your customers — someone they loop in early, not after something breaks

What We're Looking For

• Field-Facing Engineering Experience: 1–3 years in a technical role where you owned deployment or integration work in customer or enterprise environments — implementation engineering, integration engineering, applied engineering, or similar. You've built things that actually ran in production at someone else's company.
• Technical Skills: Comfortable working with Python and SQL. You know how to debug integrations when they break in the field. AI Fluency: Current on where AI tooling is heading and has applied it in actual work. You're not just familiar with the concepts — you've shipped something with it.
• Communication: Strong written and verbal communication. You'll document customer needs, brief Engineering regularly, and be the person customers trust to translate technical complexity into something actionable.

Why Monte Carlo

• You'll see your work in the product: Integrations you prototype in the field directly inform what Engineering builds next — no gap between what you learn and what ships
• Real scope, early in your career: Small team, live customer deployments from day one — not a shadow program or a rotation
• The space is growing: Every enterprise deploying agents needs reliability infrastructure underneath — Monte Carlo is building that layer
• Direct line to Engineering: What you learn in the field goes directly to the people who can act on it
• Built to grow: Integrations engineering + field experience + AI fluency is a rare combination; you'll leave with all three
• Competitive compensation, equity, and a remote-first environment