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操作画面は日本語です。企業が掲載した求人の職種名や説明文は原文のまま表示され、英語の場合があります。

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Forward Deployed Engineer

MLabs

勤務地
San Francisco, California, United States
掲載日
2026年10月20日

応募する前に、企業のウェブサイトで現在も募集中かどうかと詳しい条件を確認してください。

仕事内容

操作画面は日本語です。企業が掲載した求人の職種名や説明文は原文のまま表示され、英語の場合があります。

Location: Hybrid (NYC) - Remote (United States) Compensation: $149K - $185K Our client is a high-growth technology organization building an advanced AI platform designed for enterprise operations and value creation in an AI-native world. Founded by experienced leaders in applied AI and mission-critical infrastructure, the organization leverages a proven track record of developing leading risk management and financial infrastructure that has processed trillions in volume. Backed by top-tier venture capital firms with over $65 million in funding, the company maintains an agile, elite team focused on solving technically ambitious problems. Operating with a culture centered on high-agency, talent-dense individual contributors, our client emphasizes high autonomy, meaningful ownership, and strong judgment over hierarchy. They are seeking a Forward Deployed Engineer to own the technical customer journey and turn complex enterprise challenges into high-value, production-grade AI solutions. In this high-impact role, the successful candidate will bridge technical strategy and customer execution—partnering closely with product, sales, and engineering leaders to guide strategic clients from technical discovery through implementation, production rollout, adoption, and scaling. Key Responsibilities End-to-End AI Deployments: Own strategic client engagements throughout the lifecycle, including technical discovery, scoping, architecture design, hands-on implementation, evaluation, production rollout, and long-term adoption. Pre-Sales & Solution Architecture: Partner with the commercial team during pre-sales phases to lead technical discovery, design tailored AI solutions, and perform validation for high-value customer opportunities. Post-Sales Technical Execution: Drive post-sales success by building and integrating production AI systems that transition clients from initial concept into full production environments. Production AI Systems Engineering: Develop scalable AI applications utilizing modern large language models (LLMs), model APIs, tool calling, retrieval-augmented generation (RAG), context management, structured outputs, and agentic workflows. Product Optimization & Feedback Loops: Translate recurring customer insights into product enhancements—identifying cross-deployment patterns and developing reusable components, playbooks, tooling, and core product features. Proactive Problem Solving: Identify operational and technical opportunities, formulate strong architectural points of view, and execute without requiring rigid direction. Basic Qualifications Experience: 5+ years of experience as a Forward Deployed Engineer, Solutions Engineer, Sales Engineer, Founding Engineer, or Product Engineer with significant end-to-end customer ownership. Execution Track Record: Proven history of taking ambiguous client challenges from initial discovery through to production deployment and measurable business impact. Technical & Commercial Judgment: Strong ability to evaluate trade-offs across client needs, product features, engineering complexity, cost, and latency. Core Technical Stack: Proficiency with Python and/or Rust, React/TypeScript, SQL, APIs, system integrations, authentication protocols, cloud infrastructure, and production observability. AI & LLM Expertise: Hands-on experience building AI-powered applications, including working with model APIs, context management, tool integration, retrieval architectures, model evaluation, and performance optimization. Location & Work Style: Based in the United States or Europe for remote arrangements (NYC-based candidates will work in-office 2–3 days per week). High agency and comfort operating autonomously in fast-paced, ambiguous environments. Preferred Qualifications Travel Flexibility: Ability to travel up to 30% annually for in-person team collaboration and client engagements. Communication: Exceptional written and verbal English communication skills, with the ability to articulate complex technical architecture to both technical and executive audiences. Performance Tuning: Familiarity with profiling tools, optimization techniques, and low-latency system design. Competitive Total Compensation: Base salary range of $149,000 – $185,000, plus a competitive equity package aligned with performance and growth. Career Advancement: Opportunity to play a foundational role within a rapidly growing global technology organization. Workplace Flexibility: Remote options (US/Europe) or hybrid flexibility in New York City.  Interview Process Initial Screening: Introductory conversation to align on background, experience, and role expectations. Technical & Architectural Evaluation: Deep dive into software engineering fundamentals, AI systems architecture, and system design. Behavioral & Scenario-Based Review: Practical discussion focused on client facing scenarios, technical trade-offs, and forward-deployed problem-solving. Final Leadership Alignment: Conversations with key leadership stakeholders across Product, Sales, and Engineering. Due to the high volume of applications we anticipate, we regret that we are unable to provide individual feedback to all candidates. If you do not hear back from us within 4 weeks of your application, please assume that you have not been successful on this occasion. We genuinely appreciate your interest and wish you the best in your job search. Commitment to Equality and Accessibility: At MLabs, we are committed to offer equal opportunities to all candidates. We ensure no discrimination, accessible job adverts, and providing information in accessible formats. Our goal is to foster a diverse, inclusive workplace with equal opportunities for all. If you need any reasonable adjustments during any part of the hiring process or you would like to see the job-advert in an accessible format please let us know at the earliest opportunity by emailing human-resources@mlabs.city. MLabs Ltd collects and processes the personal information you provide such as your contact details, work history, resume, and other relevant data for recruitment purposes only. This information is managed securely in accordance with MLabs Ltd’s Privacy Policy and Information Security Policy, and in compliance with applicable data protection laws. Your data may be shared only with clients and trusted partners where necessary for recruitment purposes. You may request the deletion of your data or withdraw your consent at any time by contacting legal@mlabs.city.

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必須条件と歓迎条件を分けて確認し、勤務時間、報酬、勤務地が掲載されている場合は目を通しましょう。リモート勤務でも、居住国、就労資格、勤務時間帯が指定されることがあります。現在の募集状況と詳しい条件は企業に確認してください。

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仕事探しに関するよくある質問

英語の求人が表示されるのはなぜですか?

職種名や説明文は企業が作成したものです。条件や要件を変えないように原文を掲載しています。操作画面とこのガイドは日本語です。日本語の検索で見つからない場合は、「software engineer」のように、掲載言語の職種名やスキル名でも検索してみてください。検索語が自動翻訳されるわけではありません。

リモート求人なら、どの国からでも働けますか?

必ずしもそうではありません。居住国、就労資格、勤務時間帯が指定されている場合があります。元の求人ページで条件を確認してください。記載がない場合は、自分の居住地から応募できると判断する前に企業へ確認しましょう。リモートという表示だけでは、勤務地の制限がないことは分かりません。

検索結果が出ない場合はどうすればよいですか?

より一般的な職種名や一つのスキルで検索し、条件を一つずつ外してみてください。同じような仕事でも企業によって呼び方が異なります。特定の求人が見つからなくなった場合は、企業の採用ページで求人番号を探しましょう。検索条件を広げても、終了した募集が再開するわけではありません。

ResumizeAIから応募が送信されますか?

応募ボタンは外部サイトを開きます。企業または採用サービスの案内に従い、そのサイトで送信を完了してください。ResumizeAIで応募書類を作成しただけでは応募は送信されません。リンク先が企業のトップページの場合は、該当する募集を探してから手続きを進めましょう。

応募書類とカバーレターはどう調整すればよいですか?

募集要件と、自分が説明できるプロジェクト、業務、成果を結び付けます。経験していない技術や実績を加えず、関連する経験を分かりやすく示してください。カバーレターでは応募理由を具体例とともに伝えます。指定された言語とファイル形式に従い、送信前に両方の書類を確認しましょう。