AI Data Engineer
$81,400–$151,800 year
Remote · United States or Michigan, United States
Job Summary
Design and implement reliable, scalable data ingestion and integration pipelines for structured, semi-structured, unstructured data (databases, files, documents, APIs, events, multi-modal) that are AI-ready, governed, secure, and observable. Apply data quality, validation, monitoring, and testing in production pipelines, enforce governance and RBAC, monitor performance, troubleshoot failures, and optimize cost/throughput. Integrate AI services (document processing/understanding, embeddings, search, LLM APIs) into production workflows. Build, automate, and maintain ETL/ELT pipelines with cloud-native services; develop production-grade Python services with REST APIs to expose data and AI capabilities. Collaborate with leadership to translate vision into executable plans, develop feature engineering pipelines for ML and GenAI use cases (including RAG), establish AI data engineering standards, and drive reusable frameworks. Lead cross-functional alignment of data input/output requirements and ensure clear definitions across teams.
Required Qualifications
- 1-3 years practical experience building and deploying production-grade data pipelines
- 3-5 years experience sourcing data from storage services (AWS S3, Azure Blob), APIs, data warehouses, data lakes
- 1-3 years experience building feature stores and data marts for ML applications
- 3-5 years experience in data lineage tracking and data quality
- 3-5 years experience in data governance best practices (PII detection, data masking, RBAC)
- 3-5 years experience with Gen AI use cases (LLMs, RAG, embeddings)
- Must have tech stack – Python, Azure Data Factory, Azure Functions, Prompt engineering, Cosmos DB
- Nice to have: multi-modal data pipelines, leadership experience, CI/CD, Terraform/Azure tooling
- Experience with Azure, AWS, GCP, synthetic data generation
- Experience with multi-agent orchestration
- Experience with Terraform, Cloud formation, Bicep, Azure fabric
- Location: Hybrid with MI office and remote options
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