AI Full Stack Engineer

Lenovo — Malaysia · Posted ~22 hours ago

Mid Full-time

Skills

full-stack development AI engineering software development AI Full Stack Development

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Summary ✨ AI‑Generated

Develop full-stack solutions incorporating artificial intelligence capabilities. Work across software layers to create intelligent, scalable applications for modern technology environments.

Highlights

Opportunity to work on large-scale AI technology initiatives and contribute to innovative products and services.

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. 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. AI Performance OptimizationHallucination 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. Customer Engagement DeliveryParticipate 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 We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, color, sex, age, religion, sexual orientation, gender identity, national origin, status as a veteran, and basis of disability or any federal, state, or local protected class.