AI Data Engineer
Core
Designing and building dependable, scalable data ingestion and integration pipelines for structured, semi-structured, unstructured, and multi-modal data sources to ensure data is AI-ready, governed, secure, and observable.
Role type
Senior AI Data Engineer
Builds
Enterprise-grade, cloud-native AI solutions and data pipelines for a financial services bank
Domain
Financial Services / Cloud-Native AI / Data Engineering
Deliverable
production ML models | product features | infrastructure
Required skills
AI/ML engineering, AI agent development, multi-agent systems, Microsoft Azure services, Python, CI/CD pipelines, Terraform, CDK, monitoring and observability, ETL/ELT pipelines, REST APIs, feature engineering, RAG
Preferred skills
Azure AI Engineer certification, Azure AI Foundry, agent taxonomy and labeling, enterprise platform layers (identity, access control, registry), financial services industry knowledge
Technologies
Azure, CI/CD, Cloud, ETL, GitHub, LLM, Python, REST, Terraform
Responsibilities
Design and build data ingestion and integration pipelines for diverse data sources; Apply data quality, validation, monitoring, and testing frameworks in production; Integrate AI services (document understanding, embeddings, search, LLM APIs) into production workflows; Build and maintain ETL/ELT pipelines using cloud-native services; Develop production-grade Python services and REST APIs; Create feature engineering pipelines for ML and GenAI use cases including RAG; Own standards, best practices, and reusable frameworks for consistency and quality.
Seniority
Senior, hands-on IC
