Cake Job Search

About BTSE: 彼特思方舟 is a specialized service provider dedicated to delivering a full spectrum of front-office and back-office support solutions, each of which are tailored to the unique needs of global financial technology firms. 彼特思方舟 is engaged by BTSE Group to offer several key positions, enabling the delivery of cutting-edge technology and tailored solutions that meet the evolving demands of the fintech industry in a competitive global market. BTSE Group is a leading global fintech and blockchain company that is committed to building innovative technology and infrastructure. BTSE empowers businesses and corporate clients with the advanced tools they need to excel in a rapidly evolving and competitive market. BTSE has pioneered numerous trading technologies that have been widely adopted across the industry, setting new benchmarks for innovation, performance, and security in fintech. BTSE’s diverse business lines serve both retail (B2C) customers and institutional (B2B) clients, enabling them to launch, operate, and scale fintech businesses. BTSE is seeking ambitious, motivated professionals to join our B2C and B2B teams. About the opportunity: BTSE is a leading cryptocurrency exchange committed to delivering a world-class trading experience. As we scale our AI adoption across the business, we are looking for an AI Enablement Engineer to sit at the intersection of technology, product, and people — helping every team unlock the practical value of AI tools in their day-to-day work. In this mid-level, hands-on role you will partner with Department Heads, business stakeholders, and engineers to understand their workflows and translate those needs into working AI solutions. Whether that means building a custom AI skill to automate a reporting workflow for a Head of Department, coaching a developer on advanced Claude Code usage, or writing an AI agent that integrates with internal systems, you will be the person who makes it happen. You will work across our two enterprise AI platforms — Google Gemini (bundled with Google Workspace) and Claude Enterprise (Anthropic) — driving measurable adoption, building reusable artefacts, and upskilling colleagues at all levels of the organisation.Responsibilities AI Adoption Stakeholder Enablement Partner with Department Heads and business stakeholders to identify workflow pain points, assess AI applicability, and design and deliver tailored AI solutions using Google Gemini and Claude Enterprise. Build and maintain a library of reusable AI skills, prompt templates, and custom instructions for common business functions across departments such as finance, compliance, operations, and customer support. Plan, deliver, and iterate on AI training sessions, workshops, and onboarding materials for both business and technical audiences; track adoption metrics and report progress to management. Developer Enablement Embed with engineering teams to coach developers on effective AI-assisted development practices, including advanced Claude Code usage, prompt patterns, and MCP server integrations that improve engineering productivity. Design, build, and maintain AI agents and automated workflows that integrate enterprise AI capabilities with internal systems via REST APIs and MCP servers. Security, Governance Compliance Ensure all AI solutions and integrations are designed and deployed in alignment with BTSE’s information security policies, data handling standards, and regulatory obligations; work closely with the Information Security team to review AI use cases for data classification and acceptable use compliance. Maintain documentation of approved AI tools, integration patterns, and usage guidelines; contribute to AI governance artefacts such as acceptable use policies, risk assessments, and audit trail requirements. Programme Management Reporting Own the AI enablement programme roadmap: prioritise initiatives across departments, manage concurrent workstreams, communicate status to leadership, and measure outcomes against defined adoption and productivity KPIs. Stay current with the rapidly evolving AI tool landscape; evaluate new capabilities across our enterprise platforms, run proof-of-concept pilots, and make evidence-based recommendations on expansion or new tooling. Requirements: 3+ years of experience in a technical role such as solutions engineer, developer advocate, technical consultant, or software engineer, with a strong focus on AI/ML tooling or enterprise enablement. Hands-on experience with Claude Enterprise (claude.ai) and/or the Anthropic API, including working with system prompts, tool use, and multi-turn conversations. Practical knowledge of Google Gemini for Workspace (Docs, Sheets, Gmail, Meet) and the ability to guide end users in applying it effectively to business tasks. Ability to design and build reusable AI skills, custom instructions, and prompt templates tailored to specific business functions (e.g. finance reporting, compliance summaries, customer support drafting). Demonstrated ability to engage with non-technical stakeholders, conduct workflow discovery sessions with Department Heads, and translate business requirements into AI-powered solutions. Ability to work alongside software engineers, providing guidance on effective use of AI-assisted development tools such as Claude Code, and recommending prompt patterns or agentic workflows that improve engineering productivity. Programming proficiency in at least one language (Python, Java, Go, or JavaScript) sufficient to build proof-of-concept integrations, automation scripts, and AI agent workflows. Familiarity with REST APIs and the ability to integrate AI capabilities into existing internal tooling or workflows via API calls. Experience facilitating training sessions, workshops, or knowledge-sharing sessions on AI tools and best practices for mixed-audience groups (business users and technical staff). Strong written and verbal communication skills; able to document AI solutions clearly for both end-user guides and technical handover. Able to effectively listen, speak, read and write in English, with Chinese as a plus. Nice to haves: Familiarity with Model Context Protocol (MCP) — either consuming existing MCP servers or building custom ones to extend AI tool access to internal systems. Exposure to vector databases, embeddings, or RAG pipelines (e.g. pgvector, Chroma, or similar) for grounding AI outputs in company-specific knowledge. Knowledge of information security principles and data handling requirements in a regulated industry (fintech, crypto, or financial services); understanding of how to apply AI tools within a data governance framework. Background in change management or organisational adoption programmes; experience measuring and reporting on software or AI adoption KPIs. Familiarity with the fintech or cryptocurrency domain — understanding of common workflows across operations, compliance, customer support, and engineering teams. Prior experience authoring internal knowledge bases, wikis (e.g. Confluence), or developer-facing documentation for AI tools and processes. Perks and Benefits Competitive total compensation package Various team building programs and company events Comprehensive healthcare schemes for employees and dependants And many more! Apply and let us tell you more! #LI-MC1

Google welcomes people with disabilities.Minimum qualifications: Bachelor's degree in Science, Technology, Engineering, Mathematics, or equivalent practical experience 8 years of experience in providing production-grade AI solutions to external or internal customers with L400-level in Python, and architecting AI systems on cloud platforms. Experience in leading technical discovery sessions with executive stakeholders and engineering teams to define AI and hardware infrastructure requirements. Experience in building full-stack solutions that interface with enterprise systems. Ability to communicate in Japanese and English fluently to interact with internal and external stakeholders. Preferred qualifications: Master’s degree or PhD in AI, Computer Science, or a related technical field. Experience in implementing multi-agent systems using frameworks (e.g., LangGraph, CrewAI, or Google’s Agent Development Kit (ADK)) and patterns like self-reflection, and hierarchical delegation. Knowledge of Large Language Model (LLM)-native metrics (e.g., tokens, cost-per-request) and techniques for optimizing state management and granular tracing. Ability to implement secure agentic workflows incorporating MCP, tool-calling, and OAuth-based authentication. About the jobIn this role, you will be an embedded builder who bridges the gap between frontier Artificial Intelligence (AI) products and production-grade reality within customers. You will manage blocker to production including solving the integration issues, data readiness issues, and state-management tests that prevent AI from reaching enterprise-grade maturity. You will be providing deployment of AI systems and act as a feedback loop, translating field insights into Google Cloud’s future product roadmap.Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.Responsibilities Serve as the lead developer for AI applications, transitioning from prototypes to production-grade agentic workflows (e.g., multi-agent systems, Master Control Program (MCP) servers) that drive Return on Investment (ROI). Architect and code the connections between Google’s AI products and customer's live infrastructure, including Application Programming Interfaces (APIs), legacy data silos, and security perimeters. Build evaluation pipelines and observability frameworks to ensure agentic systems meet requirements for accuracy, safety, and latency. Identify repeatable field patterns and technical friction points in Google’s AI stack, converting them into reusable modules or formal product feature requests for the Engineering teams. Drive engineering excellence across Japan and Asia Pacific (JAPAC) region by mentoring talent, co-building with customer teams to instill best practices, and collaborating in cross-functional strategies to up-level organizational technical capabilities. Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

Google will be prioritizing applicants who have a current right to work in Singapore, and do not require Google's sponsorship of a visa.Minimum qualifications: Bachelor's degree in Science, Technology, Engineering, Mathematics, or equivalent practical experience. 6 years of experience in providing production-grade AI solutions to external or internal customers, and experience architecting AI systems on cloud platforms. Experience leading technical discovery sessions with executive stakeholders and engineering teams to define AI and hardware infrastructure requirements. Ability to communicate in Mandarin fluently to support client relationship management in this region. Preferred qualifications: Master’s degree or PhD in AI, Computer Science, or a related technical field. Experience implementing multi-agent systems using frameworks (e.g., LangGraph, CrewAI, or Google’s ADK) and patterns like ReAct, self-reflection, and hierarchical delegation. Knowledge of Large Language Model (LLM)-native metrics (e.g., tokens/sec, cost-per-request) and techniques for enhanvcing state management and granular tracing. Ability to implement agentic workflows incorporating Model Context Protocol (MCP), tool-calling, and OAuth-based authentication. About the jobIn this role, you will be an embedded builder who bridges the gap between Artificial Intelligence (AI) products and production-grade reality for customers. You will manage blockers to production including solving the integration complexities, data readiness issues, and state-management tests that prevent AI from reaching enterprise-grade maturity. You will lead the deployment of AI systems and act as a feedback loop, transforming field insights into Google Cloud’s future product road map.Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.Responsibilities Serve as the lead developer for the AI applications, transitioning from prototypes to production-grade agentic workflows (e.g., multi-agent systems, MCP servers) that drive return-on-investment. Architect and code the connections between Google’s AI products and customers' live infrastructure, including APIs, legacy data silos, and security perimeters. Build evaluation pipelines and observability frameworks to ensure agentic systems meet requirements for safety. Identify repeatable field patterns and technical friction points in Google’s AI stack, converting them into reusable modules or formal product feature requests for the engineering teams. Co-build with customer engineering teams to instill Google-grade development best practices, ensuring project success and end-user adoption. Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

Google は、障がい者採用の取り組みを進めています。必要な条件/経験:科学、テクノロジー、工学、数学のいずれかの学士号を取得していること（同等の実務経験でも可）。Python で L400 レベルの知識があり、本番環境レベルの AI ソリューションを社内外の顧客に提供した経験、およびクラウド プラットフォームで AI システムを設計した経験が 8 年以上あること。経営幹部クラスのステークホルダーやエンジニアリング チームとの技術的調査のセッションを主導し、AI とハードウェア インフラストラクチャの要件を定義した経験。エンタープライズ システムと連動するフルスタック ソリューションを構築した経験。日本語と英語による優れたコミュニケーション能力を備え、社内外の関係者とスムーズにやり取りできること。 望ましい経験/スキル:AI、コンピュータ サイエンス、または関連する技術分野における修士号または博士号。マルチエージェント システムを、フレームワーク（LangGraph、CrewAI、Google の Agent Development Kit（ADK）など）と自己反省や階層的委任などのパターンを使用して実装した経験。大規模言語モデル（LLM）ネイティブの指標（トークン、リクエストあたりの費用など）および状態管理と詳細なトレースを最適化する手法に関する知識。MCP、ツール呼び出し、OAuth ベースの認証を組み込んだ安全なエージェント ワークフローを実装できること。 この求人についてこの職種では、最先端の AI プロダクトとお客様の実際の本番環境グレードとのギャップを埋めるために、客先常駐で構築に従事していただきます。AI がエンタープライズ グレードに成熟するのを妨げる統合やデータ準備の問題、状態管理テストを解決し、本番環境への移行を阻む要因を管理します。AI システムのデプロイを提供するほか、現場の分析情報を Google Cloud の将来のプロダクト ロードマップに反映させるフィードバック ループの役割も果たします。Google Cloud は、あらゆる組織のビジネスと業界におけるデジタル トランスフォーメーションを加速させるとともに、Google の最先端テクノロジーを活用したエンタープライズ クラスのソリューションと、デベロッパーがよりサステナブルに構築に取り組めるツールを提供します。200 以上の国や地域のお客様が、成長を可能にし、最も重大なビジネス上の問題を解決するための信頼できるパートナーとして、Google Cloud を採用しています。業務内容AI アプリケーションのリード デベロッパーとして、投資収益率（ROI）を向上させる本番環境グレードのエージェント型ワークフロー（マルチエージェント システム、マスター コントロール プログラム（MCP）サーバーなど）への、プロトタイプからの移行を主導する。Google の AI プロダクトと顧客の現在のインフラストラクチャ（アプリケーション プログラミング インターフェース（API）、従来のデータサイロ、セキュリティ境界など）との間の接続を設計およびコーディングする。エージェント システムが精度、安全性、レイテンシの要件を確実に満たすように、評価パイプラインとオブザーバビリティ フレームワークを構築する。Google の AI スタックにおける繰り返し可能なフィールドのパターンと技術的な摩擦点を特定し、再利用可能なモジュールや、エンジニアリング チーム向けの正式なプロダクト機能要求にする。人材の指導、顧客チームとの共同ビルドによるベスト プラクティスの浸透、部門横断的な戦略下での連携を通じて、日本およびアジア太平洋（JAPAC）地域全体で優れたエンジニアリングを推進し、組織の技術力を向上させる。 Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Gurgaon, Haryana, India; Bengaluru, Karnataka, India; Mumbai, Maharashtra, India.Minimum qualifications: Bachelor’s degree in Science, Technology, Engineering, Mathematics, a related technical field, or equivalent practical experience. 8 years of experience in providing production-grade AI solutions to external or internal customers with L400-level in Python, and architecting AI systems on cloud platforms. Experience leading technical discovery sessions with executive stakeholders (C-suite) and engineering teams to define AI and hardware infrastructure requirements. Experience building full-stack solutions that interface with enterprise systems. Preferred qualifications: Master's degree or PhD in Computer Science, AI, Machine Learning, or a related technical field. Experience in implementing multi-agent systems using frameworks (e.g., LangGraph, CrewAI, or Google’s Agent Development Kit (ADK)) and patterns like ReAct, self-reflection, and hierarchical delegation. Knowledge of Large Language Model (LLM)-native metrics (e.g., tokens/sec, cost-per-request) and techniques for optimizing state management and granular tracing. Ability to implement secure agentic workflows incorporating Model Context Protocol (MCP), tool-calling, and Open Authorization (OAuth)-based authentication. About the jobThe Google Cloud Platform team helps customers transform and build what's next for their business — all with technology built in the cloud. Our products are developed for security, reliability and scalability, running the full stack from infrastructure to applications to devices and hardware. Our teams are dedicated to helping our customers — developers, small and large businesses, educational institutions and government agencies — see the benefits of our technology come to life. As part of an entrepreneurial team in this rapidly growing business, you will play a key role in understanding the needs of our customers and help shape the future of businesses of all sizes use technology to connect with customers, employees and partners. As a Forward Deployed Engineer (FDE) at Google Cloud, you will be an embedded builder who bridges the gap between frontier AI products and production-grade reality within customers. Unlike traditional advisory roles, you will function as an innovator-builder, moving beyond high-level architecture to code, debug, and jointly ship bespoke agentic solutions directly within the customer’s environment.In this role, you will need to be a high-agency engineer with a founder’s mindset. You will address blockers to production, including solving the integration complexities, data readiness issues, and state-management issues that prevent AI from reaching enterprise-grade maturity. By embedding with accounts, you will serve a dual purpose: providing white-glove deployment of AI systems and acting as a critical feedback loop, transforming real-world field insights into Google Cloud’s future product roadmap.Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.Responsibilities Serve as the lead developer for Artificial Intelligence (AI) applications, transitioning from rapid prototypes to production grade agentic workflows (e.g., multi-agent systems, Model Context Protocol (MCP) servers) that drive measurable Return on Investment (ROI). Architect and code the 'connective tissue' between Google’s Artificial Intelligence (AI) products and customer's live infrastructure, including Application Programming Interfaces (APIs), legacy data silos, and security perimeters. Build high-performance evaluation pipelines and observability frameworks to ensure agentic systems meet requirements for accuracy, safety, and latency. Identify repeatable field patterns and technical 'friction points' in Google’s AI stack, converting them into reusable modules or formal product feature requests for the Engineering teams. Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

Google will be prioritizing applicants who have a current right to work in Singapore, and do not require Google's sponsorship of a visa.Minimum qualifications: Bachelor's degree in Science, Technology, Engineering, Mathematics, or equivalent practical experience. 7 years of experience in cloud computing or a technical customer-facing role, with experience in Python. 2 years of experience managing a software engineering, forward deployed engineering team, or a similar direct technical customer-facing team in a cloud computing environment. Experience in developing AI/Generative AI solutions utilizing AI Tools and designing multi-agent workflows and Retrieval-Augmented Generation (RAG) systems. Preferred qualifications: Master's degree in Computer Science, Engineering, or a related technical field. Experience in designing interfaces for AI and agentic systems, prioritizing context engineering, transparency, and explainability to foster user trust. Experience in architecting AI solutions within infrastructures, and ensuring data sovereignty and secure governance. Ability to perform deep discovery interviews to find the business problem and translate hardware/AI constraints for C-suites and technical teams. Ability to design secure, observable multi-agent systems using design patterns (ReAct, self-reflection,etc), state management, and tool-calling protocols. About the jobAs the Manager of the Forward Deployed Engineering team, you will lead a team of Forward Deployed Engineers across Southeast Asia, Australia and New Zealand who bridge the gap between the AI products and production-grade reality within customers. You are responsible for a team that doesn't just consult, but codes, debug and together deploys bespoke agentic solutions directly within customer environments.In this role, you will provide technical mentorship to the team while balancing alignment with Product, Engineering, and Google Cloud Regional Sales leadership. Your mission is to empower and unblock your team as they resolve production-level obstacles, including data readiness issues, integration complexities, and state-management challenges that hinder AI from achieving enterprise-grade maturity.Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.Responsibilities Serve as the technical lead, establish code standards, architectural best practices, and benchmarks to elevate engineering excellence across the team. Partner with Sales and Tech Leadership to define requirements for opportunities, deploy specialized experts (MLOps, GenMedia, or Agentic systems) to key accounts. Lead technical hiring for the Forward Deployed Engineering team, evaluate AI/ML, systems engineering, and coding skills to build an excellent Engineering team. Identify skill gaps in emerging tech (MCP, tool-calling, and foundation models), and ensure the team maintains subject-matter-expertise in an evolving AI stack. Collaborate with Product and Engineering teams to resolve blockers and translate field insights into road maps while building internal tools to drive organizational efficiency. Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

【關於這個角色】核心任務是打通 LLM 與應用程式之間的溝通橋樑。你需要使用 Java 實作 Model Context Protocol (MCP Server)，讓 AI Agent 能夠安全、標準化地存取我們的資料與工具。 【你將面臨的挑戰】 Protocol Implementation: 開發與優化 MCP Server，確保與 LLM Client 端的通訊順暢且低延遲。Backend Development: 負責 API 的設計與實作，處理複雜的資料流邏輯與外部 API 整合。System Stability: 透過 Docker 容器化技術確保環境一致性，並透過完整的測試代碼（Unit/Integration Test）保障系統品質。

介紹 GNTC 團隊Dcard GNTC 團隊致力於打造企業級 AI 工作平台，讓企業都能透過 AI 提升工作效率、創造更高價值。我們相信 AI 不只是工具，更是每個團隊成員的智能助手，能夠深度整合企業資料與流程，協助團隊做出更精準的決策、產出更高品質的成果。我們提供全方位的企業 AI 工作平台，使企業夥伴可以提升決策與洞察 、加速企劃產出 ，並且能透過 Agent 自動化處理例行任務，讓團隊專注於更具創造性與決策價值的工作。為了達成這個目標，我們需要 Forward Deployed Engineer 加入我們，你將駐點或遠端與企業客戶深度合作，從業務需求拆解、原型設計，到雲端部署與維運，端到端交付生成式 AI 解決方案。歡迎加入這個熱愛挑戰的技術團隊，一起打造被千萬人喜愛與使用的產品！ 你將在團隊參與⋯ 基於 Dcard GNTC Agent 平台設計技術方案，並以現場 (on site) 或遠端 (remote) 的方式與企業客戶深度合作，從業務需求拆解、原型設計，到雲端部署與維運，端到端交付生成式 AI 解決方案。與客戶 BU／IT 團隊進行訪談，定義 Problem Statement 與 KPI負責理解用戶現行流程與痛點，並提出可行的技術解決方案。以 TypeScript（或 Python）實作 API／MCP／Agent 等 Workflow，協助用戶在其既有系統中導入與整合。撰寫技術白皮書、實踐手冊 (Playbook)，回饋產品 Roadmap 與最佳實踐 (best practice)

介紹 GNTC 團隊 Dcard GNTC 團隊致力於打造企業級 AI 工作平台，讓企業都能透過 AI 提升工作效率、創造更高價值。我們相信 AI 不只是工具，更是每個團隊成員的智能助手，能夠深度整合企業資料與流程，協助團隊做出更精準的決策、產出更高品質的成果。我們提供全方位的企業 AI 工作平台，使企業夥伴可以提升決策與洞察 、加速企劃產出 ，並且能透過 Agent 自動化處理例行任務，讓團隊專注於更具創造性與決策價值的工作。為了達成這個目標，我們需要 Fullstack Engineer 加入我們，負責 Dcard GNTC 企業 Agent 平台的前後端開發與系統架構設計。你將端到端打造完整的生成式 AI 應用，為企業客戶提供優質的產品體驗。 你將在團隊參與⋯ 開發 Dcard GNTC Agent 平台的前後端完整功能設計並實作 AI Chat 介面、Dashboard、管理後台等前端應用開發 MCP Server、API、AI Workflow 等後端服務整合 LLM、RAG 等 AI 技術棧優化前端使用者體驗與後端系統效能根據產品規劃與客戶需求，快速交付完整的技術方案參與技術方案討論，從前端到後端提供完整的實作建議將產品需求轉化為清晰的前後端功能與使用者體驗根據時程、成本、技術可行性平衡前後端開發優先順序持續改善產品體驗與技術架構優化前端互動體驗、效能與可用性強化後端系統的穩定性、可擴展性與維護性建立可重用的 UI 元件與後端模組改善開發工具、CI/CD 與部署流程技術研究與知識分享持續學習 Agent 相關知識與前後端新技術，評估並導入適合的技術在團隊內部進行技術分享與文件撰寫

介紹 GNTC 團隊 Dcard GNTC 團隊致力於打造企業級 AI 工作平台，讓企業都能透過 AI 提升工作效率、創造更高價值。我們相信 AI 不只是工具，更是每個團隊成員的智能助手，能夠深度整合企業資料與流程，協助團隊做出更精準的決策、產出更高品質的成果。我們提供全方位的企業 AI 工作平台，使企業夥伴可以提升決策與洞察 、加速企劃產出 ，並且能透過 Agent 自動化處理例行任務，讓團隊專注於更具創造性與決策價值的工作。為了達成這個目標，我們需要 Senior Backend Engineer 加入我們，負責 Dcard GNTC 企業 Agent 平台的後端架構設計、AI 模型整合與系統開發。你將專注於打造穩定、可擴展的生成式 AI 後端服務，為企業客戶提供強大的技術支撐。 你將在團隊參與⋯ 設計與開發 Dcard GNTC Agent 平台的後端系統設計並實作 MCP Server、API、AI Workflow整合 LLM、Vector Database、RAG 等 AI 技術優化系統效能、可靠性與可擴展性根據產品規劃與客戶需求，設計並實作技術方案參與技術方案討論，根據時程、成本、技術可行性提出建議將產品需求轉化為清晰的技術架構與實作持續改善平台架構與開發體驗全面瞭解整體系統架構，識別並優化架構建立可復用的技術元件與最佳實踐改善 CI/CD、監控、部署流程技術研究與知識分享持續學習 Agent 相關知識與新技術，評估並導入適合的技術在團隊內部進行技術分享與文件撰寫