Our mission is to automate coding. The first step in our journey is to build the best tool for professional programmers, using a combination of inventive research, design, and engineering. Our organization is very flat, and our team is small and talent dense. We particularly like people who are truth-seeking, passionate, and creative. We enjoy spirited debate, crazy ideas, and shipping code.
About the role
Forward Deployed Engineers embed directly with customer engineering teams to ship production-grade Cursor workflows that measurably improve how they build software.
You’ll figure out what’s actually slowing a team down, design a practical solution, and own it end-to-end, from first discovery call through launch, iteration, and post-production support. This is not a demo role. You are responsible for systems that work in the real world.
What you’ll do
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Lead discovery with customer engineers to identify the real bottleneck and define clear success metrics
Ship a fast first version in days, then harden it into something reliable over weeks with proper rollout plans, monitoring, and iteration based on real usage
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Own production quality: tracing, evals, metrics, debugging model behavior, latency/cost tradeoffs, and failure modes
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Work directly with Staff+/Platform/Eng leaders — going deep in code while also communicating clearly about tradeoffs and results
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Turn what you build into reusable patterns and push improvements back into the core Cursor product
You may be a fit if
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You have 5+ years of experience with software development and coding in Python, Javascript/Typescript
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Experience includes 2+ years in a customer-facing role, leading discovery conversations and being accountable for customer outcomes
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You thrive in ambiguity and can turn fuzzy problems into clear scopes and shipped systems
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You’ve built and owned AI-native workflows in production, not just prototypes, and have debugged real-world model failures
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You build end-to-end - if it needs frontend, backend, infra, or prompt iteration, you’ll own it
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You’ve handled production reliability before (metrics, alerts, safe rollouts, incident response)