AI Data Specialist

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 #196 in the Fortune Global 500, and serving millions of customers every day in 180 markets. Guided by its vision of “Smarter Technology for All”, Lenovo is executing a Hybrid AI strategy that spans Personal AI – one personal AI, multiple devices;

and Enterprise AI – helping customers turn data into insights and value. This strategy is delivered through the Group’s commitment to world‑class innovation and a full‑stack AI portfolio, including devices (PCs, workstations, smartphones, tablets, accessories), infrastructure solutions (server, storage, edge, high performance computing and software defined infrastructure), as well as software, solutions, and services. With a global footprint spanning 21 research and development locations in 11 markets, and a global supply chain including more than 30 manufacturing sites across 10 markets, Lenovo is widely recognized for its operational excellence, including ranking #8 in the Gartner Supply Chain Top 25.

Lenovo is listed on the Hong Kong stock exchange under Lenovo Group Limited (HKSE: 992) (ADR: LNVGY).

As an AI Data Specialist, you will play a key role in the design, development, and deployment of an Agentic AI platform that streamlines the creation of AI‑driven customer solutions. You will work closely with AI engineers and cross‑functional teams to support the deployment, integration, and scaling of AI services across enterprise environments. In this role, you will leverage your expertise in data management, AI technologies, and development practices to build efficient, reusable, and scalable data‑driven solutions.

You will be responsible for ensuring that data pipelines, models, and AI components are effectively integrated into a cohesive and high‑performing platform. To succeed, you should possess a strong understanding of AI and data ecosystems, demonstrate hands‑on technical skills, and have the ability to transform complex data and AI tools into standardized, repeatable solutions that drive business value.

This role sits within Lenovo’s Solutions Services Group (SSG), the global organization that brings together our end‑to‑end AI solutions and services to turn customer vision into value. You’ll be joining a new, distributed engineering team building the xIQ Agent Platform, an AI‑native delivery platform that powers Lenovo’s Agentic AI strategy across hybrid cloud, on‑prem, and edge.

• Design, develop, and implement data‑driven AI solutions for an Agentic AI platform, aligning with enterprise architecture and business objectives.
• Build and maintain scalable data processing pipelines for AI workloads, including data ingestion, cleansing, transformation, and feature engineering.
• Develop and deploy end‑to‑end AI systems using LLMs, SLMs, and VLMs for advanced data processing, enrichment, and automation.
• Leverage NVIDIA AI technologies (e.g., CUDA, NV‑Ingest, VLM…) or similar platforms to optimize model training, fine‑tuning, and inference performance.
• Implement and manage vector databases such as Milvus, Postgre
  
  SQL (PGVector), or other vector stores to support semantic search, embeddings, and Retrieval‑Augmented Generation (RAG) use cases.
• Design and optimize data and retrieval pipelines that integrate structured and unstructured data with LLM‑based reasoning systems.
• Develop and integrate AI components (APIs, microservices, inference layers) into enterprise platforms across cloud, on‑premise, and edge environments.
• Select and implement data engineering and pipeline orchestration tools to ensure scalable and reliable data workflows.
• Apply best practices in data engineering, MLOps, and AIOps, including pipeline monitoring, versioning, and performance tuning.
• Ensure data security, governance, and compliance, including encryption, access control, and secure data handling practices.
• Write clean, maintainable, and reusable code following enterprise development standards and best practices.
• Create detailed technical documentation, including data flow architectures, pipeline designs, model integration…