What are the responsibilities and job description for the Data Engineer with AI position at Lumiere Systems?
Applicants must be authorized to work in the United States on a full-time basis without the need for current or future visa sponsorship.
No third-party agencies, recruiters, or staffing firms will be considered for this position.
Role Summary
We are seeking a senior Data Engineer to design and build enterprise-scale data platforms that enable AI/ML and agentic systems. This role focuses on engineering AI-ready data foundations—ensuring data is high-quality, governed, and optimized for advanced analytics and autonomous AI agents.
Key Responsibilities
No third-party agencies, recruiters, or staffing firms will be considered for this position.
Role Summary
We are seeking a senior Data Engineer to design and build enterprise-scale data platforms that enable AI/ML and agentic systems. This role focuses on engineering AI-ready data foundations—ensuring data is high-quality, governed, and optimized for advanced analytics and autonomous AI agents.
Key Responsibilities
- Architect and build scalable, cloud-native data platforms supporting AI/ML and agent-based applications
- Design pipelines to deliver AI-ready data (curated, labeled, contextualized, and feature-rich datasets)
- Develop robust data ingestion, transformation, and serving layers (batch real-time)
- Enable semantic data models, knowledge graphs, and vector databases to power AI agents and LLMs
- Implement data quality, lineage, and governance frameworks to ensure trust and compliance
- Collaborate with AI/ML teams to support feature engineering, model training, and inference pipelines
- Optimize data architectures for performance, scalability, and cost efficiency
- Mentor teams and establish best practices for AI-driven data engineering
- 10 years of experience in data engineering and platform architecture
- Strong expertise in cloud platforms (Azure, AWS, or GCP) and modern data ecosystems
- Familiarity with AI/ML data pipelines, feature stores, and model lifecycle support
- Experience with LLM data pipelines
- Strong understanding of data governance, metadata management, and security frameworks
- Experience building data platforms for AI agents / agentic workflows
- Knowledge of RAG (Retrieval Augmented Generation) architectures and semantic search
- Exposure to data mesh / domain-oriented data architectures
- Experience in large-scale enterprise transformation programs