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# Senior AI Data Engineer

- **Company:** HCL GLOBAL
- **Location:** New York, NY, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** A/B Testing, Artificial Intelligence, Amazon Web Services, Microsoft Azure, Data Distribution Service, Information Engineering, Data Infrastructure, Database Queries, Distributed Systems, Graph Database, Python (Programming Language), Neo4j, Open Source Technology, Azure Machine Learning, Explainable AI (XAI), Feature Engineering, Retrieval-Augmented Generation, Apache Spark, Google Vertex AI, Generative AI, Build Management, Data Lineage, Deployment Automation, HuggingFace, Machine Learning Operations, Virtual Agents, Drift Detection, Model Registry, Software Version Control, Data Pipelines, Databricks
- **Published:** October 8, 2026
- **Apply:** https://www.disabledperson.com/jobs/75918473-senior-ai-data-engineer

## About the Role

? 10+ years of overall experience

? 5+ years of hands-on Data Engineering experience

? 2+ years working with AI/ML workloads

? Strong Python expertise

? Databricks, Apache Spark & distributed computing

? Strong understanding of ML lifecycle: training, deployment & monitoring

? Feature engineering and ML data pipelines

? MLflow / Model Registry / Experiment Tracking

? Strong SQL skills

? Experience with vector databases, embeddings & similarity search

? Understanding of data/model governance and AI security

? Nice to Have

 * Generative AI / RAG / Fine-tuning
 * LangChain / HuggingFace
 * MCP experience
 * Azure ML / AWS SageMaker / Google Vertex AI
 * Neo4j / Amazon Neptune / Knowledge Graphs
 * AI explainability & interpretability
 * ML A/B testing frameworks
 * Databricks / AWS / Azure / GCP certifications
 * Open-source ML contributions or publications

## Description

* Design and build AI/ML data pipelines for model metadata, data lineage, and performance tracking
 * Build scalable data infrastructure using Databricks & Apache Spark
 * Develop MCP servers and enable AI data distribution through MCP
 * Build feature engineering and data preprocessing pipelines
 * Implement MLflow for experiment tracking, model versioning, and model registry
 * Develop AI agent discovery, classification, and inventory workflows
 * Design knowledge graphs for AI model relationships, dependencies, and data lineage
 * Build real-time pipelines for model monitoring, drift detection, and performance tracking
 * Implement AI-specific data quality, governance, security, and compliance frameworks
 * Collaborate closely with Data Scientists, ML Engineers, and Architects