- Kuala Lumpur Federal Territory Malaysia
Kerja Sepenuh Masa, AI Full Stack Engineer di Lenovo Federal Territory - Maukerja
Kongsi
Simpan
Lokasi Kerja
Penerangan Kerja
Tanggungjawab
General Information
Req #
WD00103202
Career area:
Hardware Engineering
Country/Region:
Malaysia
State:
Wilayah Persekutuan Kuala Lumpur
City:
Kuala Lumpur
Date:
Tuesday, August 18, 2026
Working time:
Full-time
Additional Locations:
- Malaysia
Why Work at Lenovo
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 *************, and read about the latest news via our StoryHub.
Description and Requirements
Summary- We are seeking a highly motivated Finance AI Full Stack Engineer to design, develop, and deploy AI-powered finance solutions for enterprise customers.
Key Responsibilities
- Design and develop end-to-end AI applications leveraging - Large Language Models (LLMs).
- Retrieval Augmented Generation (RAG).
- Multi-Agent Systems, Workflow Automation
- Develop front-end applications and user interfaces.
- Build backend services and APIs.
- Design scalable microservice architectures.
- Integrate AI services into enterprise applications.
- Build secure and production-grade solutions.
- Design enterprise knowledge bases.
- Develop RAG pipelines.
- Build document processing and semantic search capabilities.
- Integrate structured and unstructured finance data.
- Design ontology and knowledge graph models for finance domains.
- Integrate AI applications with: o SAP ECC / S4HANA o Oracle ERP o Microsoft Dynamics o Data Platforms o Workflow Systems
- Develop APIs and middleware services.
- Enable real-time and batch integrations.
5. AI Performance Optimization
- Hallucination Control, Latency, Cost Efficiency, User Experience
- Implement evaluation frameworks and testing methodologies.
- Participate in customer workshops.
- Support solution demonstrations and PoCs.
- Translate business requirements into technical solutions.
- Drive end-to-end solution delivery.
- Provide technical guidance during implementation.
6. Customer Engagement & Delivery
- Participate in customer workshops.
- Support solution demonstrations and PoCs.
- Translate business requirements into technical solutions.
- Drive end-to-end solution delivery.
- Provide technical guidance during implementation.
Qualification & Experience
- 3–6 years of hands-on full-stack software engineering experience, with proven delivery of production-grade LLM / Generative AI / Agent / RAG applications; POC-only experience is insufficient.
- Strong proficiency in Python and at least one modern frontend framework, such as React, Next.js, Vue or Angular.
- Practical experience integrating LLM APIs and building prompt-engineering, RAG, tool-calling or agent-based workflows, with a solid understanding of model limitations, hallucination risks, context management and output reliability.
- Hands-on experience developing backend services and APIs using frameworks such as FastAPI, Flask, Django, Node.js or equivalent, including authentication, authorization, error handling and asynchronous processing.
- Practical experience with data ingestion, document processing, embeddings, vector search and databases such as PostgreSQL, Elasticsearch or a vector database.
- Demonstrated experience delivering SaaS features across the full software-development lifecycle, including requirements clarification, technical design, implementation, testing, deployment, monitoring and production support
Additional Locations:
- Malaysia
- Malaysia
Peringatan Penting
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