FDE has become a hot role in tech — here are the lessons we learned from scaling it at Ramp to win enterprise.
Overview
This article explores the rise of Forward Deployed Engineering (FDE) as a strategic role in B2B tech companies, tracing its origins from Palantir to its current adoption across companies like OpenAI, Anthropic, Databricks, and Ramp. It covers Ramp's experience building and scaling their FDE team from 2 to 16 engineers, including their operating model, core principles, and hiring philosophy for customer-facing engineering roles.
What You'll Learn
What Forward Deployed Engineering is and how it originated at Palantir before spreading across the B2B tech industry
Why enterprise-focused B2B companies need FDE teams and how they drive faster growth rates
How to structure an FDE team's operating model around the customer lifecycle from sales to long-tail support
How to apply core FDE principles like 'always be scoping' and balancing generalization vs. quick fixes
How to hire effective FDEs by evaluating drive, engineering fundamentals, customer empathy, and communication skills
Prerequisites & Requirements
- Understanding of B2B SaaS business models and enterprise software sales
- Familiarity with software engineering team structures and roles
- Basic understanding of enterprise customer lifecycle (sales, implementation, support)(optional)
Key Questions Answered
What is a Forward Deployed Engineer and where did the role originate?
Why is Forward Deployed Engineering growing so fast in 2025?
How should an FDE team be structured around the customer lifecycle?
What are the core principles of a successful FDE team?
What should you look for when hiring Forward Deployed Engineers?
How does scoping save engineering time in FDE?
When should FDE teams build generalized features vs. quick customer-specific hacks?
How should FDE teams prioritize their work?
Key Statistics & Figures
Technologies & Tools
Key Actionable Insights
1Map your FDE team to the full customer lifecycle rather than siloing by function. Engineers should work with customers from the sales funnel through implementation to long-tail support, maintaining context and continuity throughout. This prevents knowledge loss during handoffs and ensures engineers understand the full picture of customer needs.Ramp found that lifecycle mapping enables early scoping, better relationships, and accountability for long-term success rather than just hitting implementation milestones.
2Adopt the 'always be scoping' mentality by having engineers talk directly to customers and question every requirement before building. Many customer requests can be solved with workarounds, reduced scope, or creative alternatives that save days or weeks of engineering effort.Ramp shares a specific example where a 3-day estimated feature gap was eliminated entirely by hopping on a call and finding a workaround. This principle prevents the common anti-pattern of mega-projects that lag behind schedule.
3When hiring FDEs, prioritize drive and work ethic above technical perfection. Candidates who performed just okay in coding interviews can become incredible FDEs if they have hustle, ownership, and customer empathy. AI tooling makes it easier than ever to learn and execute on technical problems.Ramp explicitly states drive is the single best predictor of real-world FDE performance. They also look for signals like previous founder experience (7 of 16 FDEs are former founders), teaching experience, and roles enabling others.
4Balance generalization against quick customer fixes with deliberate judgment. Prefer building general features and platforms because ad-hoc customizations pollute the codebase, increase entropy, and decrease maintainability — but recognize that sometimes the MVP hack is the right choice to unblock a customer quickly.This tension between scoping down and building scalable solutions is described as where the 'taste and skill' of an FDE are most crucial, requiring constant judgment calls.
5Follow a three-tier prioritization for your FDE team: first serve existing customers well to prevent churn and generate positive references, then increase onboarding efficiency since implementation is typically the enterprise bottleneck, and finally expand product capabilities to grow your TAM.Ramp developed this prioritization hierarchy as their team grew from a small firefighting squad into a structured organization, moving from 'falling behind' to 'innovating' on Will Larson's model of team states.
6Leverage AI tools like Cursor and Claude Code to accelerate FDE team output. Use GenAI projects to build platform functionality that scales your ability to serve complex enterprise customer needs, rather than relying solely on manual engineering effort.Ramp's FDE team describes AI as a crucial part of their recent growth, with GenAI projects deployed across all of their pods to build platform functionality.