Description

You will design and implement enterprise-grade data architectures and end-to-end pipelines for generative AI applications.

This role is hybrid.

Responsibilities

• Design and develop end-to-end data pipelines from ingestion through deployment and monitoring.
• Lead the architecture of complex agentic frameworks and optimized RAG architectures.
• Implement strategies for handling unstructured data and designing graph database solutions.
• Integrate data pipelines with Snowflake and collaborate with teams to embed solutions.
• Mentor junior data engineers on development best practices.

Required Skills

• 10+ years in data engineering, with at least 3 years focused on Generative AI.
• Expertise in DB Architecture and production-ready enterprise data pipelines.
• Deep knowledge of VectorDBs, graph databases, NoSQL, and Document DBs (e.g., Cosmos DB, MongoDB, DynamoDB, Neo4j).
• Proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow.
• Experience with cloud platforms including Azure, AWS, or GCP.
• Hands-on experience with containerization using Docker and Kubernetes.
• Strong expertise in PostgreSQL and processing unstructured data.

Preferred Skills

• Ability to explain complex technical concepts to technical and non-technical stakeholders.

Key Skills

Education

Any Graduate