Lenovo is a US$69 billion revenue global technology powerhouse, ranked #196 in the Fortune Global 500, and serving millions of customers every day in 180 markets. Focused on a bold vision to deliver Smarter Technology for All, Lenovo has built on its success as the world’s largest PC company with a full-stack portfolio of AI-enabled, AI-ready, and AI-optimized devices (PCs, workstations, smartphones, tablets), infrastructure (server, storage, edge, high performance computing and software defined infrastructure), software, solutions, and services. Lenovo’s continued investment in world-changing innovation is building a more equitable, trustworthy, and smarter future for everyone, everywhere. Lenovo is listed on the Hong Kong stock exchange under Lenovo Group Limited (HKSE: 992) (ADR: LNVGY).
This transformation together with Lenovo’s world-changing innovation is building a more inclusive, trustworthy, and smarter future for everyone, everywhere. To find out more visit www.lenovo.com, and read about the latest news via our StoryHub. Description and Requirements
Job Responsibilities:
Develop and maintain core modules of the AI platform, such as model development, RAG-based knowledge systems, and agents.
Work with architects and senior engineers to implement scalable and modular GenAI solutions.
Integrate GenAI frameworks (e.g., LangChain, LangGraph) with backend infrastructure and APIs.
Participate in the design, coding, testing, and deployment of AI features in both cloud-native and hybrid environments.
Contribute to the automation of model training, deployment, and monitoring workflows.
Write clean, maintainable code and collaborate with cross-functional teams in an agile environment.
Job Requirements:
- Bachelor’s degree in Computer Science, Software Engineering, Artificial Intelligence, or a related field.
- 3+ years of experience in backend or AI platform development.
- Proficient in Java and Python, with experience in Spring and Spring Cloud.
- Familiar with PostgreSQL, MySQL, and common data storage formats and access patterns.
- Experience using Docker, Kubernetes, Git, and CI/CD tools.
- Understanding of DevOps and Scrum practices.
- Familiarity with GenAI technologies such as transformers, model fine-tuning, inference, RAG, or intelligent agents.
- Experience working with LangChain, LangGraph, or similar open-source GenAI frameworks.
- Exposure to real-world GenAI application development (e.g., chatbots, copilots, document Q&A systems) is a plus.
- Understanding of model deployment and monitoring practices is a bonus.