---
title: 'Forward Deployed Engineer - Japan at Cursor'
canonical: 'https://feeny.ai/job/forward-deployed-engineer-japan-cursor-japan-n2z1ybx7y9p5'
type: 'job'
last_seen: '2026-10-13'
---

# Forward Deployed Engineer - Japan at Cursor

- **Company:** Cursor
- **Location:** Japan
- **Employment:** full-time
- **Work type:** remote
- **Posted:** 2026-10-09
- **Last confirmed live:** 2026-10-13
- **Apply:** https://jobs.ashbyhq.com/cursor/38bd03a3-3d65-4868-87df-cb248d0a45e3

## Job description

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

You embed directly with customer teams as the engineer on the ground: own an outcome, ship a production-grade SpaceXAI system that still runs after you leave, and become the critical technical feedback loop from the field back to product engineering. The work is the project. One week you might take a messy business workflow and put a production agent on it: pick the use case, stand up the architecture, wire it into the customer’s auth, data, and tools, then harden it with evals until the team actually uses it. Another week you might live in a customer’s repo and delivery system and ship an agent-powered path for a migration, a PR review loop, or an incident-to-fix flow, behind tests, review, and rollout rather than in a chat sidebar. Either way, you measure what matters, leave the customer able to operate it, and bring the pattern back as another use case for SpaceXAI. This is not a demo role. You own the work end to end, from the first discovery call through launch, iteration, and post-launch support, and you are responsible for systems that work in the real world.

## What you’ll do

- Lead discovery with the customer: orient in their codebases and workflows, find the real bottleneck and the use case worth building, and define clear success metrics
- Design and ship production agents, AI applications, and coding-agent workflows on Grok and our models, on live business processes and inside the customer’s engineering org
- Get a first version live in days, then harden it over weeks with rollout, monitoring, and iteration from real usage
- Own production quality: tracing, evals, debugging model or delivery failures, and latency and cost tradeoffs
- Build the systems around the model (tools, MCP servers, retrieval, rules, skills, CI gates, and evals) and integrate them into the customer’s auth, data, workflow, and delivery systems; decide when prompting, architecture, data, process, or a model change is the right lever
- Measure the outcome that matters (revenue, cost, hours saved, error rate, cycle time, escaped defects), not seat adoption
- Work directly with Staff+, platform, and domain leaders, going deep in their systems while communicating clearly about tradeoffs and results
- Leave the customer team able to run what you built, and turn what you learn into reusable patterns and improvements to SpaceXAI products

You may be a fit if Required

- You have 5+ years of experience in software engineering, machine learning engineering, or data science
- You write and review production code (Python, JavaScript/TypeScript; other languages welcome)
- You’ve owned a customer or operator outcome, not just a slide or a prototype, and can turn a fuzzy problem into a scoped, shipped system
- You’ve built and owned AI-native workflows or agents in production, and debugged real production failures (model, tool, data, pipeline, or delivery path)
- You’ve handled production reliability: metrics, alerts, safe rollouts, incident response
- You build end to end: frontend, backend, infra, and prompt iteration
- You thrive in ambiguity and don’t need a complete spec before you start building
- You can talk to working engineers and to a VP
- Fluency in both Japanese and English

## Nice to have

- 2+ years in a customer-facing role, leading discovery conversations and being accountable for outcomes for external stakeholders
- Hands-on depth in several of: agents and tool-calling, eval harnesses, retrieval and context systems, CI/CD or developer platforms, and AI-native coding workflows in a real repo
- Experience as a forward-deployed, solutions, or platform engineer embedded with customers, or as a founding engineer who owned an AI product end to end

## About Cursor

## Company Overview
- **One-liner**: Cursor is an AI coding agent and software development environment that enables developers to build, test, and ship software using natural-language instructions and autonomous agents.
- **Entity Type**: Private (pending acquisition by SpaceX/xAI)
- **Headquarters**: San Francisco, California, United States
- **Founded**: 2022
- **Founders**: Michael Truell, Sualeh Asif, Aman Sanger, Arvid Lunnemark

## Core Business
- **Primary industry**: Artificial intelligence, developer tools, software development
- **Target customers**: B2B (enterprise, SMB, individual developers); trusted by over half of the Fortune 500
- **Mission/purpose**: To build the future of software development and help engineers "engineer anything"

## Products & Services
- **Cursor (AI Coding Agent)**: The flagship product — an AI-powered code editor and agent that searches codebases, edits files, runs terminal commands, and completes multi-step programming tasks from natural-language instructions. Available as a desktop IDE, web app, mobile app (iOS), and CLI.
- **Bugbot**: A code-review tool integrated with GitHub pull requests that autonomously detects bugs and issues.
- **Composer Models**: A family of proprietary agentic coding models (Composer, Composer 1.5, Composer 2, Composer 2.5) trained with reinforcement learning for long-running coding tasks.
- **Cursor Automations**: Always-on agents that run on schedules or triggers to build, maintain, and fix software.
- **Cloud Agents**: Agents that run in their own cloud environments to build, test, and demo features end-to-end.
- **Graphite**: A separate product acquired by Cursor (formerly a stack-based Git workflow tool).

## Market Standing
- **Valuation**: $29.3 billion (Series D, November 2025); pending acquisition by SpaceX/xAI at $60 billion (announced June 16, 2026)
- **Key Metric**: $3 billion+ Annual Recurring Revenue (ARR) as of May 2026
- **Notable Investors**: Accel, Coatue Management, Thrive Capital, OpenAI Startup Fund, Google, Nvidia; angel investors include Nat Friedman (former GitHub CEO) and Arash Ferdowsi (Dropbox co-founder)
- **Growth Signals**: Crossed $100M ARR in Jan 2025, $500M ARR by June 2025, $1B ARR by Nov 2025, and $3B ARR by May 2026. Headcount grew from ~300 (2025) to 579 (mid-2026). Expanding into mobile, Jira integration, and enterprise features.

## Competitive Advantages
- **Proprietary coding models (Composer series)** trained with reinforcement learning specifically for software development tasks — a deep technical moat
- **Complete codebase understanding** at any scale, enabling agents to work contextually across large, complex codebases
- **Multi-model flexibility**: Integrates models from OpenAI, Anthropic, Gemini, xAI, and their own models, letting users choose the best tool per task
- **Agentic infrastructure**: Agents that run autonomously, in parallel, and across environments (terminal, Slack, GitHub, Jira, cloud)
- **Massive adoption**: Trusted by over half the Fortune 500 and millions of developers — strong network effects and brand lock-in

## Strategic Focus
- **Scaling agentic capabilities**: Moving from assisted coding to fully autonomous software development agents
- **Enterprise expansion**: Building admin controls, SSO, compliance features, and usage analytics for large organizations
- **Platform ecosystem**: Expanding into adjacent tools (Jira, Slack, GitHub, mobile) to embed agents everywhere developers work
- **Model research**: Continued investment in training frontier coding models with reinforcement learning and synthetic data
- **Post-acquisition integration with xAI**: Leveraging SpaceX/xAI compute and infrastructure for even larger models

## Why Work Here
- **Mission-driven research environment**: Cursor describes itself as "an applied research team focused on building the future of software development" — a rare blend of R&D and product engineering
- **Talent density**: The company "obsesses over talent to an unusual degree" and designs itself as "a haven for self-motivated individual contributors"
- **Rapid growth trajectory**: From 0 to $3B ARR in ~4 years — employees work on products used by millions and see massive scale
- **Compensation**: Competitive for AI/engineering talent; top-of-market salaries and equity in a high-valuation private company
- **Work policy**: Mix of in-office (San Francisco, New York) and remote roles; many engineering roles are on-site
- **Engineering culture**: Two-day on-site final interviews with the core team; no AI tools allowed in first-round coding interviews — they value raw problem-solving
- **Team composition**: 579 employees with strong talent density from Stripe, Figma, Notion, Vercel, Graphite, Slack, Rubrik, and Plaid
- **Recent departures to**: Anthropic, OpenAI, Google, AWS — alumni are highly sought after

## Sources
1. [cursor.com](https://cursor.com)
2. [cursor.com/careers](https://cursor.com/careers)
3. [LinkedIn](https://www.linkedin.com/company/cursorai)
4. [Wikipedia](https://en.wikipedia.org/wiki/Cursor_(company))
5. [JobsByCulture](https://jobsbyculture.com/blog/working-at-cursor-2026)

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- [Field Marketing Manager](https://feeny.ai/job/field-marketing-manager-cursor-japan-n78ech7ma68z) — Japan
- [Integrated Campaigns, APJ](https://feeny.ai/job/integrated-campaigns-apj-cursor-australia-2yg2rpw5yg3q) — Australia
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- [Forward Deployed Engineer - EMEA](https://feeny.ai/job/forward-deployed-engineer-emea-cursor-london-f7y1wdx5yrng) — London, United Kingdom
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