Junior Applied Forward Deployed Engineer (FDE)

Monte Carlo Data, Inc.

Job Overview

Location

Remote, US

Job Type

Full-time

Full Job Description

📋 Description

• Work directly with enterprise customers to understand their data environments, AI integration needs, and technical gaps in production AI systems, then translate those requirements into functional prototypes.
• Build custom integrations and connectors using Python, SQL, and REST APIs to connect Monte Carlo’s platform with customer data stacks including Snowflake, Databricks, Salesforce, and other enterprise systems.
• Conduct rapid field testing of prototypes in live customer environments, shipping solutions quickly, validating real-world performance, and iterating based on observed outcomes.
• Document findings from customer engagements, including what integration patterns worked, what failed, and why — and relay these insights directly to Engineering and Product teams to inform core product development.
• Collaborate with senior Forward Deployed Engineers to transition proven customer-specific solutions into scalable, productized features that become part of Monte Carlo’s official platform.
• Serve as a trusted technical contact for customers, engaging early in their AI deployment cycles to prevent issues and provide guidance — not just responding to breaks after they occur.
• Prototype solutions that bridge the gap between what customers need today and what Monte Carlo will ship tomorrow, ensuring the product evolves based on real, field-validated demand.
• Operate in a remote-first environment with direct exposure to live customer deployments from day one, with no shadow programs or rotational assignments.
• Engage with a wide variety of enterprise data architectures, gaining hands-on experience with AI tooling in production settings across industries such as healthcare, financial services, and enterprise SaaS.
• Maintain clear, actionable written and verbal communication with both customers and internal engineering teams, translating technical complexity into actionable feedback loops.
• Stay current on the latest AI agent tooling and apply that knowledge to real deployment scenarios — not just theoretical understanding, but shipped, field-tested implementations.
• Work in a small, high-velocity team focused on field engineering, with no internal tooling or abstract development; all work is customer-facing and directly impacts product direction.
• Gain exposure to three active customer integrations (Salesforce, PennyMac, OGE Healthcare) as proof of concept, and help scale this model to additional enterprise accounts.
• Participate in the full lifecycle of field deployments: from initial customer discovery, through build and test, to handoff and documentation — ensuring solutions are reproducible and scalable.

🎯 Requirements

• 1–3 years of field-facing engineering experience in deployment, integration, or implementation roles within customer or enterprise environments
• Hands-on proficiency with Python and SQL, and demonstrated ability to work with REST APIs in live, production environments
• Practical experience applying AI tooling in real-world work, not just conceptual familiarity
• Strong written and verbal communication skills with ability to document customer needs and relay technical insights to engineering teams
• Experience building and debugging integrations in production systems, not just tutorials or sandbox environments
• Comfort working autonomously in a fast-paced, unstructured environment where processes are defined by field outcomes, not pre-set workflows

🏖️ Benefits

• Competitive compensation and equity package
• Remote-first work environment with no location requirements within the U.S.
• Direct line to Engineering and Product teams — field insights directly shape product roadmap
• Opportunity to build rare, high-value skills in integrations engineering, field experience, and AI fluency
• Early career exposure to real customer deployments and product impact, not rotational or shadow programs
• Access to a fast-growing AI reliability infrastructure space with clear market demand

Skills & Technologies

Python

Spring

REST

Junior

Remote

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Monte Carlo Data, Inc.

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About Monte Carlo Data, Inc.

Monte Carlo Data, Inc. provides a data observability platform that monitors data pipelines, detects anomalies, and alerts teams to data quality issues across warehouses, lakes, and ETL systems. It automates lineage tracking, impact analysis, and root-cause investigation to reduce downtime and improve trust in analytics and machine-learning outputs. The company serves data engineers, analysts, and data scientists in finance, e-commerce, healthcare, and technology sectors, integrating with Snowflake, Databricks, BigQuery, Redshift, and Airflow to deliver real-time reliability metrics and governance controls.

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