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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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Lead Solutions Architect, AI Build & Delivery (Remote, Any Location, US)

Foundever

リモート勤務

勤務地
Remote (United States)
勤務時間
Full Time
掲載日
2026年10月12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。

About Foundever: Foundever™ is a global leader in the customer experience (CX) industry. With 170,000 associates across the globe, we are the team behind the best experiences for +750 of the world’s leading and digital-first brands. Our innovative CX solutions, technology and expertise are designed to support the operational needs of our clients and deliver a seamless experience to customers in the moments that matter. Job Summary We are building an AI Professional Services practice from the ground up. We need a technically savy Lead Architect who can own the build end-to-end: from client brief to working prototype, from prototype to production, and from solo contributor to the technical anchor of a growing team. This is a rare founding opportunity. You will personally ship the first solutions, establish what great AI delivery looks like at Foundever, and grow into a Tech Lead role as the practice scales. You will work closely with Sales, Product, and client stakeholders — bringing engineering credibility and realistic delivery judgment to every engagement. WHAT YOU'LL DO 1. Client Delivery & Technical Build Be the primary builder in every early client engagement — take a scoped brief to a working prototype within days, not weeks Design and deliver tailored AI solutions using LLMs, agents, RAG pipelines, and AI-assisted development workflows — from discovery through go-live Build live demos and proof-of-concepts that directly support deal closure, working alongside commercial stakeholders Own technical quality across all solutions: security, scalability, maintainability, and production readiness Lead the transition of delivered solutions to production — including monitoring, cost control, reliability, and support handoff Apply responsible AI delivery standards: data privacy, model selection, prompt and version management, and safeguards where required 2. Commercial & Scoping Judgment Assess client needs and determine the best solution path: EverSuite capability, off-the-shelf tooling, or custom AI build Estimate build costs with precision — time, infrastructure, tooling, and ongoing maintenance Join client scoping sessions and technical discovery calls, bringing engineering credibility and realistic timelines Flag reusable solution patterns that can evolve into packaged service offerings Partner with Sales to scope, price, and validate new services opportunities from a technical standpoint 3. Product Feedback Loop Identify recurring custom client requests that signal mid-term product opportunities Communicate technical insights clearly and actionably to Product Managers Define what "productizable" looks like technically — providing the feasibility foundation for roadmap decisions Feed client insights back into the EverSuite roadmap through structured cross-functional collaboration 4. Practice Building Document architecture patterns, reusable components, and build playbooks from day one Establish delivery methodologies and quality standards for AI implementations Create repeatable offerings: AI discovery workshops, rapid prototyping packages, paid pilots, and managed AI solution support As the team grows, step into a Tech Lead role — setting technical standards, reviewing work, and mentoring junior architects and engineers Define technical hiring criteria for future team members WHAT WE'RE LOOKING FOR Must-Haves 7+ years in solutions architecture, software engineering, or technical consulting — ideally in an AI, data, or SaaS context Strong hands-on track record building and shipping solutions — not just designing them Deep fluency with AI-assisted development workflows (Cursor, Copilot, Claude, v0, Replit, etc.) — you build with these tools daily Solid understanding of LLM application patterns: RAG, agents, prompt engineering, tool use, and fine-tuning Strong engineering judgment — you know when to move fast and when production readiness requires slowing down Ability to present your own work clearly to both technical teams and non-technical client stakeholders Proven ability to estimate, scope, and defend technical build decisions commercially Demonstrated ability to operate autonomously and lead without a fully formed team around you Nice-to-Haves Background in enterprise software, cloud platforms, or AI/ML infrastructure Experience in a startup, scale-up, or zero-to-one environment — comfortable building without a playbook Familiarity with MLOps, vector databases, or AI safety considerations Prior experience influencing a product roadmap from field or client insights Exposure to P&L ownership, SOW management, or professional services revenue models Background in BPO, CX, or contact center technology Experience in regulated industries where responsible AI is non-negotiable WHAT "AI BUILD FLUENCY" MEANS HERE This isn't an architecture-on-paper role. We expect our Lead Architect to personally ship working software — not just produce diagrams and hand off to others. You use AI-assisted development tools as a force multiplier, not a crutch. You review AI-generated code critically, make real-time architecture decisions without committee alignment, and have a clear point of view on where these tools accelerate delivery and where they introduce risk. You should be able to demonstrate all of the following: Spin up a working prototype within hours of a client brief Critically review AI-generated code — not just prompt and ship Make real-time architecture decisions without waiting for committee sign-off Scaffold, ship, and iterate on real solutions under commercial pressure Coach clients on integrating AI-assisted workflows into their development culture Maintain engineering rigor around security, scalability, and maintainability Originally posted on Himalayas

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次の仕事で活かしたい職種やスキルから検索を始めましょう。勤務地と職種の条件を調整し、求人を開いて担当業務を比較してください。結果がない場合は、短い検索語を試すか、条件を一つずつ外してみましょう。

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。

募集要件に関連する実際の経験を選び、自分の役割と貢献を説明しましょう。数値は根拠がある場合にのみ使ってください。企業の応募方法に従い、送信前に連絡先、内容、PDFの表示を確認しましょう。

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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。