Junior Applied Forward Deployed Engineer (FDE)

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 FDE team at Monte Carlo is a small, rapid-prototyping unit in the field. The team handles customer-specific technical integration requests without constraining the core product roadmap — FDEs prototype solutions, conduct rapid field testing, and relay what they learn back to Engineering and Product. McWayne is currently running three active integrations — Salesforce, PennyMac, and OGE Healthcare — as proof of concept for this model. Engineers hired into this function will expand that motion at scale.

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.

• 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

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.

Python, SQL, and APIs

Hands-on with Python and SQL. Comfortable working with REST APIs in real environments, not just in tutorials. 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 That Closes the Loop

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.

• You want to work on internal tooling with no customer contact

• You need a fully defined process before you can ship

• Your idea of field work is joining a call and writing a summary

• You're looking for a support role — this is a build role

• 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.

#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.