AI Data Specialist
About The Position
As an AI Data Specialist, you will help design, develop, and deploy an Agentic AI platform that streamlines the creation of AI-driven customer solutions. You will work with AI engineers and cross-functional teams to deploy, integrate, and scale AI services across enterprise environments. The role uses data management, AI technologies, and development practices to build efficient, reusable, and scalable data-driven solutions, and ensures that data pipelines, models, and AI components are integrated into a cohesive, high-performing platform. This is a fully remote role based in the United States. Candidates who reach the final selection stage will be invited to complete their final interview in person.
Requirements
- Bachelor’s or Master’s degree in Computer Science, Data Engineering, Artificial Intelligence, or a related field.
- At least 5 years of experience in AI/data engineering and implementation roles, including data engineering, machine learning, NLP, or Generative AI-focused data solutions.
- At least 2 years of hands-on experience building end-to-end Generative AI and data-driven solutions, including data preprocessing, embedding generation, and RAG pipelines using LLMs and multimodal models.
Nice To Haves
- 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 with the NVIDIA AI ecosystem, including GPUs, CUDA, TensorRT, or NeMo, or equivalent acceleration technologies for data processing, model training, and inference.
- Strong understanding of data architectures involving structured, semi-structured, and unstructured data, and of building scalable pipelines for AI/ML workloads.
- Experience integrating AI/data solutions across cloud and on-premise environments, including containerization and orchestration using Docker and Kubernetes.
- Experience implementing MLOps, LLMOps, and DataOps practices, including CI/CD pipelines, data versioning, monitoring, and lifecycle management using Jenkins, GitLab, MLflow, or similar tools.
- Strong Python programming skills, experience with data processing libraries such as Pandas and PySpark, and familiarity with API development.
- 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.
Responsibilities
- Design and deploy AI solutions using LLMs, SLMs, VLMs, and Agentic AI frameworks.
- Support AI architecture, solution design, and proof-of-concept initiatives.
- Build scalable data pipelines for ingestion, transformation, and enrichment.
- Develop RAG solutions using vector databases such as Milvus and PGVector.
- Integrate AI services, APIs, and microservices into enterprise platforms.
- Optimize model training and inference using GPU-accelerated technologies.
- Implement MLOps, LLMOps, and pipeline orchestration best practices.
- Monitor, optimize, and maintain AI workflows and platform performance.
- Ensure data security, governance, and compliance requirements are met.
- Create technical documentation and maintain high-quality, reusable code.
- Partner with cross-functional teams to deliver scalable AI solutions.
- Evaluate and adopt emerging AI and data technologies to improve platform capabilities.
Benefits
- Bonuses and/or commissions may be available.
- Lenovo benefits are referenced at www.lenovobenefits.com.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
