Description

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

Responsibilities

• Design and develop end-to-end data pipelines from ingestion through to 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 for complex relationships.
• Integrate data pipelines with Snowflake and collaborate with cross-functional teams to embed solutions into existing products.
• Build POCs and prototypes to evaluate emerging technologies and establish architectural patterns.
• Mentor junior data engineers and architects on development best practices.

Required Skills

• 10+ years of experience in data engineering with at least 3 years focused on Generative AI technologies.
• Expertise in DB Architecture and designing 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.
• Ability to explain complex technical concepts to both technical and non-technical stakeholders.

Key Skills

Education

Any Graduate