AI Data Engineer

About the Role

AI Data Engineer

Key Responsibilities

AI & LLM Integration

• Design and implement

  LLM-based workflows

  , including

  RAG (Retrieval-Augmented Generation)

  pipelines.
• Build

  agentic orchestration frameworks

  using tools such as

  LangChain, LangGraph, CrewAI

  , or similar.
• Integrate vector databases and embeddings for semantic search and AI-driven applications.

Data Engineering & Pipelines

• Design, develop, and maintain

  scalable, reliable data pipelines

  using

  Python

  and

  Azure services

  .
• Implement ETL/ELT workflows for structured and unstructured data.
• Optimize data ingestion, transformation, and storage for performance and cost efficiency.

Cloud & Deployment

• Deploy data and AI solutions using

  cloud-native architectures

  on

  Azure

  (preferred) or

  AWS/GCP

  .
• Containerize applications using

  Docker

  and orchestrate using

  Kubernetes

  .
• Implement CI/CD pipelines for automated build, test, and deployment.