AI Application Development Engineer

Lenovo; Kuala Lumpur; On-site; MYR 120,000 - 240,000; Full time

Job summary

Lenovo, a global technology leader, seeks an experienced AI Agent developer to design and implement enterprise-grade intelligent agents. You will lead RAG systems construction, prompt engineering, and integration with data APIs and data warehouses.

You will own end-to-end lifecycle from design to launch, optimizing architecture, recall, and accuracy while reducing hallucinations. Strong Python, FastAPI, and vector database expertise are required.

Qualifications

• Major in computer science or related fields is preferred, with a bachelor's degree or above.
• Proficient in using AI programming tools (Cursor, Copilot, GPT, Qoder, etc.), enhancing development efficiency.
• Proficient in Python; design of complex backend architectures; experience with FastAPI and design patterns.
• Strong code-writing, debugging, optimization, and engineering thinking; familiarity with Linux, Git, and Docker.
• Experience in developing RAG applications, QA systems, SQL auto-generation, or data analysis assistants.
• Familiar with AI Agent design patterns like ReAct, Plan-and-Execute, Reflection.
• Proficient with vector databases (Milvus, Chroma) and traditional databases (PostgreSQL, MySQL, Redis, Elasticsearch).
• Familiar with AI agent frameworks: LangChain/LangGraph, LlamaIndex, CrewAI, AutoGen, or Agent Framework.
• Proficient in frontend basics (Vue/React) for UI or result display pages.

Responsibilities

• Application development of AI Agent.
• Build enterprise-level intelligent agent applications (data analysis assistants, reporting systems, knowledge Q&A, automation).
• Master construction of RAG systems, including prompt engineering, vectors, embeddings, and retrieval optimization.
• Implement task planning, dialogue management, intent recognition, tool invocation, and integration using LangChain, LangGraph, LlamaIndex, and Agent Framework.
• Independently complete the entire agent lifecycle from design to launch.
• Promote optimization of AI Agent architecture and performance.
• Implement Agent-to-Agent orchestration and multi-agent collaboration for agents.
• Convert natural language into data queries (SQL/DSL) and interface with data APIs and warehouses.
• Build BI capabilities with logical analysis, field mapping, indicators, exception handling, and result interpretation.
• Collaborate with data teams to optimize data calibers, indicators, and knowledge graphs.
• Use vector retrieval (Milvus/PGVector) + structured data queries to build a hybrid RAG.
• Improve recall, data context, reduce hallucinations, and increase answer accuracy.

Skills

Python

FastAPI

Linux

Git

Docker

SQL generation

RAG applications

LangChain/LangGraph

Education

Bachelor's degree or above

Tools

Milvus

Chroma

PostgreSQL

MySQL

Redis

Elasticsearch

Docker

Git

LlamaIndex

CrewAI

Job description

We are Lenovo. We do what we say. We own what we do. We WOW our customers.

Lenovo is a US$83 billion revenue global technology powerhouse, ranked #153 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

• Application development of AI Agent
• Responsible for building enterprise-level intelligent agent applications, such as intelligent data analysis assistants, intelligent reporting systems, knowledge question answering, process automation, and other scenarios.
• Master the construction of RAG (Retrieval Augmented Generation) systems, including prompt engineering, vector databases, embeddings, and retrieval optimization strategies (hybrid retrieval, reranking, query reformulation, etc.).
• Implement task planning, dialogue management, intent recognition, tool invocation, process engineering, RAG, etc. for intelligent agents based on LangChain, LangGraph, LlamaIndex, and Agent Framework.
• Able to independently complete the entire process of an intelligent agent, from design to launch.
• Promote continuous optimization of AI Agent in terms of architecture and performance.
• Implement A2A (Agent-to-Agent) orchestration, multi-agent collaborative task design, and implementation for intelligent agents.
• Automatically convert natural language into data queries (SQL/DSL), and interface with enterprise data APIs and data warehouses.
• Build capabilities such as logical analysis, field mapping, indicator definition, exception handling, and result interpretation for intelligent BI.
• Collaborate with the data team to optimize data calibers, indicator systems, and knowledge graphs.
• Utilize vector retrieval (Milvus/PGVector) + structured data query to build a hybrid RAG
• Optimize recall, enhance data context, reduce hallucinations, and improve answer accuracy.

Job Requirements

• Major in computer science or related fields is preferred, with a bachelor's degree or above.
• Proficient in using AI programming tools (such as Cursor, Copilot, GPT, Qoder, etc.), which can significantly enhance development efficiency.
• Proficient in the Python programming language, with experience in designing complex backend system architectures, proficiency in frameworks such as FastAPI, strong software framework and application design capabilities, high-performance architecture design, and a deep understanding of design patterns.
• Possess excellent abilities in code writing, debugging, optimization, and engineering thinking; be familiar with the Linux development environment, version control Git, and Docker operations.
• Experience in developing RAG applications, question-answering systems, SQL automatic generation, or data analysis assistants.
• Familiar with the design patterns of AI Agents: ReAct, Plan-and-Execute, Reflection, etc.
• Proficient in the use of vector databases (such as Milvus, Chroma) and traditional databases (PostgreSQL, Sql Server, Mysql, Redis, Elasticsearch);
• Familiar with any of the AI agent frameworks: LangChain/LangGraph, LlamaIndex, CrewAI, AutoGen, or Agent Framework.
• Proficient in basic front-end development (Vue/React, either) for developing user interfaces or result display pages for intelligent agents.

If you require an accommodation to complete this application, please contact [e-mail]