Full Stack Engineer (Tripo Studio)

Hangzhou, BeijingExperiencedFull-time

Responsibilities

Your Responsibilities 1.You will be granted full ownership and end-to-end accountability for the design and delivery of core product modules: Full-Stack Product Development Backend: Design and build high-concurrency, low-latency core services with Go/Python/Node.js, covering task scheduling, billing systems, authentication frameworks and asynchronous workflows. Frontend: Independently develop user-facing web applications including creation workspaces, data dashboards, online 3D preview and interactive playgrounds, with a relentless focus on premium user experience. Full lifecycle ownership: You take full control over the entire tech stack, from database schema design and API contracts to CI/CD pipelines and production monitoring. 2.Integration & Innovation of AI Capabilities Deeply embed AI model capabilities (3D generation, post-processing, semantic comprehension) into product workflows, and design optimal interaction paradigms between users and AI. Leverage LLMs and Agent tools to boost engineering efficiency: automated test generation, code review, documentation generation and intelligent operations. Keep track of cutting-edge AI technologies (multimodal models, Diffusion, NeRF/3DGS), evaluate new capabilities and rapidly build prototypes to validate productization potential. 3.Platform & Infrastructure Construction Build a developer platform consisting of API gateways, SDKs, technical documentation and integration playgrounds, enabling external developers to launch a Hello World demo within 5 minutes. Support multi-end architecture (Web / App / Plugins), and design scalable BFF layers and service orchestration logic. 4.Technical Support for Commercialization Collaborate with business teams to quickly address B-end client requirements, including private deployment, dedicated compute pools and customized workflows. Drive business growth through technical approaches: A/B testing, user behavior analytics and conversion funnel optimization. 职位描述 1、你将拥有极高的 Owner 权限，端到端负责核心产品模块的设计与交付： 产品全栈开发 后端：设计并构建高并发、低延迟的核心服务（Go/Python/Node.js），涵盖任务调度、计费系统、鉴权体系和异步工作流 前端：独立开发面向用户的 Web 应用——创作工作台、数据看板、在线 3D 预览与交互 Playground，追求极致的用户体验 全链路：从数据库 schema 设计到 API 契约，从 CI/CD 到线上监控，你对整个技术栈拥有完整的掌控力； 2、AI 能力集成与创新 将 AI 模型能力（3D 生成、后处理、语义理解）深度融入产品工作流，设计 AI 与用户交互的最佳体验 利用 LLM/Agent 工具提升工程效率：自动化测试生成、代码审查、文档生成、智能运维 跟踪前沿 AI 技术（多模态模型、Diffusion、NeRF/3DGS），评估并快速原型验证新能力的产品化可能； 3、平台与基础设施 构建开发者平台：API 网关、SDK、技术文档、接入 Playground，让外部开发者 5 分钟跑通 Hello World 支撑多端架构（Web/App/Plugin），设计可扩展的 BFF 层和服务编排； 4、商业化技术支撑 与商务团队配合，快速响应 B 端客户需求（私有化部署、专属算力池、定制工作流） 用技术手段驱动增长：A/B 实验、用户行为分析、转化漏斗优化

Qualifications

Job Requirements Core Technical Hard Skills (Mandatory) 1.Full-Stack Engineering Competence Backend: Proficient in at least one language among Go, Python and Node.js. Frontend: Skilled in React or Vue, capable of independently developing visually polished web applications with complex interactions. Database: Familiar with PostgreSQL, Redis and message queues (Kafka/RabbitMQ); well-versed in data modeling and performance optimization. Infrastructure: Experienced with Docker/K8s, CI/CD pipelines and cloud services (AWS/GCP/Alibaba Cloud). 2.AI Expertise (Key Preferred Qualifications) Hands-on experience building product features or internal tools with LLM APIs (GPT/Claude/Gemini). Familiar with AI application paradigms including Prompt Engineering, RAG and Agent workflows. Basic knowledge of AI model inference deployment (model serving, GPU resource management). Prior understanding of Diffusion models, multimodal models or 3D generation technology is highly preferred. 3.System Design Capabilities Familiar with OAuth2/JWT authentication, API versioning and rate-limiting strategies. Experience integrating payment systems (Stripe / Alipay) is a plus. Solid understanding of microservice architecture, event-driven design and fundamental distributed system principles. 职位要求 1、全栈工程能力 后端：精通 Go / Python / Node.js 至少一种 前端：熟练掌握 React 或 Vue，能独立开发交互复杂、视觉精良的 Web 应用 数据库：熟悉 PostgreSQL、Redis、消息队列（Kafka/RabbitMQ），理解数据建模与性能优化 基础设施：熟悉 Docker/K8s、CI/CD 流程、云服务（AWS/GCP/阿里云）； 2、AI 技能（核心加分项） 有使用 LLM API（GPT/Claude/Gemini）构建产品功能或内部工具的实战经验 熟悉 Prompt Engineering、RAG、Agent 工作流等 AI 应用范式 了解 AI 模型推理部署基础（模型 Serving、GPU 资源管理） 对 Diffusion 模型、多模态模型、3D 生成技术有了解者优先； 3、系统设计 熟悉 OAuth2/JWT 鉴权、API 版本控制、限流策略 有对接支付系统（Stripe/支付宝）经验者优先 理解微服务架构、事件驱动设计、分布式系统基本原理

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