AI Data Engineer

The AI Data Engineer is a remote, hands-on individual contributor in Cinteot’s AI CoE Technology pod, associated with Newark, New Jersey. The role builds governed, reusable, AI-ready data foundations for enterprise generative AI and agent-based use cases. It works with AI Platform Engineers, AI Engineers and other partners to support shared platform capabilities and priority use cases.

Responsibilities

• Design, operate and optimize pipelines that ingest, transform and curate structured and unstructured data. Prepare RAG-ready datasets using metadata enrichment, chunking, normalization and document parsing; work with source-system teams and domain experts to represent data accurately.
• Generate, refresh and manage embeddings; maintain vector indexes through re-indexing, performance tuning and removal of stale embeddings. Support agent knowledge grounding with source attribution and traceability.
• Implement data-quality checks, validation and monitoring; maintain freshness, lineage and compliance with enterprise governance, privacy and information-management policies, including for sensitive or regulated data. Coordinate with Architecture, Security and Information Governance on approved patterns and risk controls.
• Diagnose data issues affecting agent behavior or retrieval accuracy, document reusable patterns and templates, support platform data-grounding activities, and improve pipeline scalability and cost efficiency. Monitor usage and recommend dataset refresh, enhancement or retirement.

Qualifications and capabilities:

• Bachelor’s degree in computer science, engineering, data science or a related technical discipline, or an equivalent combination of education and relevant experience. Demonstrated experience operating production-grade enterprise data pipelines; experience preparing documents, PDFs and text for analytics, ML, AI or search; working knowledge of embeddings, vector databases and retrieval patterns; and understanding of data quality, lineage and governance.
• The posting also calls for familiarity with cloud-native data services and AI platforms, collaboration across platform and application teams, and the ability to translate business requirements into technical solutions. It mentions regulated enterprise GenAI or agentic AI experience and healthcare compliance and ethical AI concepts. Familiarity with HIPAA, SOC 2 and HITRUST frameworks is preferred. Relevant AWS, Azure, Databricks or Snowflake certifications are a plus.

Benefits listed include medical, dental, vision and life insurance, a 401(k) contribution, paid time off including birthday PTO, paid holidays and education reimbursement.