AI Data Specialist

Lenovo; North Carolina; A distancia; USD 120.000 - 190.000; Jornada completa

Descripción de la vacante

Lenovo is seeking an AI Data Specialist to design, develop, and deploy an Agentic AI platform that streamlines AI-driven customer solutions for enterprise environments.

You will collaborate with AI engineers and cross-functional teams, build data pipelines, manage embeddings and RAG, and ensure secure, scalable architectures across cloud and on-premise environments.

This remote US role requires hands-on experience with LLMs, vector databases, MLOps, and strong data governance.

Formación

• Bachelor’s or Master’s degree in CS, AI, or related field.
• 5+ years in AI/data engineering and implementation roles.
• 2+ years building end-to-end Generative AI data solutions, incl. RAG pipelines.

Responsabilidades

• Design and deploy AI solutions using LLMs, SLMs, VLMs and Agentic AI frameworks.
• Build scalable data pipelines for ingestion, transformation, and enrichment.
• Develop RAG solutions using Milvus and PGVector.
• Integrate AI services and microservices into enterprise platforms.
• Implement MLOps, LLMOps, and pipeline orchestration best practices.
• Monitor and maintain AI workflows and platform performance.
• Create technical documentation and reusable code.
• Collaborate with cross-functional teams to deliver scalable AI solutions.

Conocimientos

Python

Data Engineering

AI/ML

Generative AI

NLP

RAG

Educación

Bachelor’s or Master’s in CS/AI or related field

5+ years in AI/data engineering

Herramientas

Milvus

PGVector

Docker

Kubernetes

GitHub

MLflow

Descripción del empleo

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.

Job Summary

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 is a remote role based in the US. Please see below for important information regarding the recruiting process for fully remote roles.

Job Responsibilities

AI Solution Development

• Design and deploy AI solutions using LLMs, SLMs, VLMs, and Agentic AI frameworks.
• Support AI architecture, solution design, and proof-of-concept initiatives.

Data Engineering RAG

• Build scalable data pipelines for ingestion, transformation, and enrichment.
• Develop RAG solutions using vector databases such as Milvus and PGVector.

AI Platform Integration

• Integrate AI services, APIs, and microservices into enterprise platforms.
• Optimize model training and inference using GPU-accelerated technologies.
• MLOps Operations
• Implement MLOps, LLMOps, and pipeline orchestration best practices.
• Monitor, optimize, and maintain AI workflows and platform performance.

Security Documentation

• Ensure data security, governance, and compliance requirements are met.
• Create technical documentation and maintain high-quality, reusable code.

Collaboration Innovation

• Partner with cross-functional teams to deliver scalable AI solutions.
• Evaluate and adopt emerging AI and data technologies to improve platform capabilities.

Basic Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, Artificial Intelligence, or a related field.
• 5+ years of experience in AI/data engineering and implementation roles, including data engineering, machine learning, NLP, or Generative AI-focused data solutions.
• 2+ years of hands‑on experience in building end-to-end Generative AI and data-driven solutions, including data preprocessing, embedding generation, and Retrieval-Augmented Generation (RAG) pipelines using LLMs and multimodal models (e.g., OpenAI, Anthropic, Llama, Hugging Face, Amazon Bedrock).

Preferred Qualifications

• Strong experience with data processing frameworks and pipeline development.
• Hands‑on experience with vector databases such as Milvus, PostgreSQL (PGVector), Pinecone, or similar, including embedding management and semantic search implementations.
• Experience working with the NVIDIA AI ecosystem (e.g., GPUs, CUDA, TensorRT, NeMo) or equivalent acceleration technologies for efficient data processing, model training, and inference is a strong plus.
• Strong understanding of data architectures involving structured, semi-structured, and unstructured data, and building scalable pipelines to support AI/ML workloads.
• Experience integrating AI/data solutions across cloud and on-premise environments, including containerization and orchestration using Docker and Kubernetes.
• Proven experience implementing MLOps, LLMOps, and DataOps practices, including CI/CD pipelines, data versioning, monitoring, and lifecycle management using tools such as Jenkins, GitLab, MLflow, or similar.
• Strong programming skills in Python, with experience in data processing libraries (e.g., Pandas, PySpark), and familiarity with API development.
• Solid understanding of data governance, security, and compliance, including handling sensitive data and implementing access controls and encryption.
• Strong problem-solving skills and ability to translate complex data and AI requirements into scalable, reusable solutions.

The Interview Process

What to expect during your interview: Our virtual interviews including phone screens are conducted on camera to support an engaging and consistent interview experience. Please ensure you have access to a camera, audio, and reliable internet connectivity. If you are unable to participate on camera, please let your recruiter know in advance.

Candidates who progress to the final stage of the selection process for fully remote roles will be invited to complete their final interview in person to learn more about Lenovo, meet key stakeholders, and experience our workplace and culture firsthand.

#Remote

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.