Advisory Full Stack Engineer, AI Orchestration

LATC Summary:

Lenovo AI Technology Center (LATC) is Lenovo's global AI Center of Excellence, fueling the enterprise's transformation into an AI-first organization. As a world-leading computing company, Lenovo offers a full spectrum of technology products and solutions, covering wearables, Motorola smartphones, ThinkPad/Yoga laptops, PCs, workstations, servers, and end-to-end services. This unparalleled product breadth creates a unique canvas for AI innovation, enabling rapid deployment of cutting-edge foundation models and flexible hybrid-cloud, agentic computing across the entire product portfolio. LATC is building the next wave of AI core technologies and platforms that evolve with the fast-moving AI ecosystem, focusing on novel model and agentic orchestration & collaboration across mobile, edge, and cloud resources. Our mission is to position Lenovo and its customers at the forefront of the global AI generational shift, advancing Lenovo's Hybrid AI vision and delivering Smarter Technology for All.

Job Summary:

As a core engineering delivery role, you will be responsible for the end-to-end engineering implementation, global cloud deployment and full-stack system optimization of Lenovo's enterprise AI systems. Focused on back-end development with matched front-end technical capabilities, you will convert the AI agent system Reference Design (prototype/demo) into production-level, deployable products, undertake hybrid cloud/edge-cloud orchestration and deployment, and ensure the stable landing and large-scale operation of AI products across Lenovo's hybrid cloud, edge and end-device ecosystem. This role is the key link connecting AI prototype development and actual business application, and is critical to the engineering realization and global delivery of LATC's Hybrid AI and agentic computing strategy.

Key Responsibilities:

Back-End Service Development: Based on the enterprise AI agentic system technical specifications and Reference Design, build enterprise-level distributed services using mainstream technical stacks; design and develop APIs and SDKs, implement core business logic, and ensure the high availability, high scalability and high performance of back-end services for AI agentic systems.

Full-Stack System Integration: Complete front-end interface development and human-computer interaction design for AI products (adapted to PC/mobile/cloud terminals); realize seamless data interaction and full-stack integration between front-end applications and back-end services, and ensure the fluency and usability of the entire system.

Hybrid Cloud & Edge-Cloud Deployment: Combine Lenovo's hybrid cloud technical architecture, complete containerization and orchestration of AI products based on Docker/K8s; implement global deployment on public cloud (AWS/Azure), private cloud and edge devices, and solve cross-regional deployment environment compatibility, network latency and resource scheduling problems.

System Performance Optimization: Optimize the running performance of AI products from the engineering level, including back-end service tuning, database query optimization, cache strategy design and front-end rendering optimization; reduce system latency, improve throughput, and adapt to the hardware performance characteristics of Lenovo's end devices/servers to achieve optimal running effect.

Deployment Documentation & Post-Delivery Maintenance: Compile detailed technical documents including product deployment manuals, operation guides and maintenance specifications; provide technical support for the post-delivery operation of enterprise AI products, track system real-time running status, and carry out version iteration and function optimization according to business needs and technical updates.

Required Qualifications:

• Bachelor's degree or above in Computer Science, Software Engineering, Computer Engineering or related technical fields. Master's Degree or PHD preferred.
• 5+ years of back-end development and enterprise-level full-stack engineering delivery experience, with experience in cloud-native/microservice system development and hybrid cloud deployment preferred; familiar with the entire software development life cycle (SDLC).
• Proficient in mainstream Java back-end technology stack:
  • Core framework: Spring Boot / Spring Cloud / Spring MVC
  • Microservice components: Nacos/Eureka (service discovery), Dubbo/Feign (service invocation), Sentinel/Hystrix (fuse & downgrade), Spring Cloud Gateway (API gateway)
  • Persistence layer: MyBatis / MyBatis-Plus / JPA; proficient in relational database design and SQL optimization (MySQL/PostgreSQL)
  • Message queue: RocketMQ / Kafka / RabbitMQ (asynchronous communication, peak clipping)
  • Development & build tools: Maven / Gradle, Git (version control), Jenkins (CI/CD)
• Proficient in at least one mainstream front-end framework and basic stack: Vue3/React/Angular; skilled in HTML5/CSS3/JavaScript/TypeScript; able to independently complete front-end page development, component encapsulation and back-end interface docking.
• Familiar with cloud-native and containerization technologies: Docker (containerization), Kubernetes (K8s, orchestration); able to build automated CI/CD pipelines and realize one-click deployment of AI systems.
• Proficiency in Linux operating system (CentOS/Ubuntu); skilled in shell script writing; able to independently complete server environment configuration, system deployment, log analysis and problem troubleshooting.

Preferred Qualifications:

• Experience in AI agent system or large model application engineering delivery; familiar with the engineering deployment characteristics of LLM/AI agent systems.
• Experience in DevOps/MLOps; able to build automated monitoring, alarming and operation and maintenance systems for AI products (Prometheus/Grafana/Zabbix); familiar with observability infrastructure design (tracing/logging/monitoring).
• Familiar with front-end visualization technologies (ECharts/Highcharts/Ant Design Pro); able to design and develop intuitive and easy-to-use AI product operation dashboards and data visualization interfaces.

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