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/
Design, develop and launch AI Agents for real‑world business workflows. Deliver production‑grade systems that serve real end‑users and continuously undertake business tasks, and take ownership of business outcomes.
Iterate continuously based on online task performance and user feedback. Improve task success rate, stability, response latency and cost through root‑cause analysis of failure cases, evaluation regression testing and execution trace troubleshooting.
Build core Agent capabilities including task planning, tool calling, context management and memory module. Integrate business systems and data, and resolve challenges such as exception recovery, state management and permission control for complex tasks.
Select and extend Agent frameworks according to business requirements, and accumulate reusable engineering capabilities and tuning best practices.
1、面向真实业务流程，负责 AI Agent 的设计、开发与上线，交付有实际用户使用、能够持续承担业务任务的系统，并对业务效果负责；
2、围绕线上任务和用户反馈持续迭代，通过失败案例分析、评测回归及执行轨迹排查，优化任务成功率、稳定性、响应速度与成本；
3、负责任务规划、工具调用、上下文管理、Memory 等核心能力建设，打通业务系统与数据，解决复杂任务中的异常恢复、状态管理和权限控制问题；
4、结合业务需求选择和扩展 Agent 框架，沉淀可复用的工程能力与调优方法。
职位要求
Hands‑on experience building production‑grade business‑facing Agents that have been launch
Job Responsibilities
1.Multi-cloud Architecture Management & Business Implementation
Take charge of the planning, construction and daily operation & maintenance of the company’s infrastructure on mainstream public clouds including AWS and Alibaba Cloud. Independently collaborate with business teams to deliver architecture design, resource planning, deployment & launch, and full-lifecycle management for complex business systems.
2.Stability Assurance of Kubernetes Clusters
Build large-scale Kubernetes clusters, optimize their stability, conduct capacity planning and fine-tune scheduling policies. Lead containerization migration of services, and troubleshoot complex issues of cloud-native components such as network and storage.
3.O&M of AI Computing Infrastructure
Ensure stable operation of large model training and inference workloads. Be proficient in driver configuration, network (InfiniBand/RoCE) and monitoring troubleshooting of heterogeneous computing servers equipped with NVIDIA GPUs, and optimize GPU resource scheduling and utilization efficiency.
4.CI/CD & Automated Pipeline Construction
Design and optimize CI/CD pipelines based on GitHub Actions, GitLab CI, ArgoCD, etc. Prom
