Description

You will engineer solutions at the intersection of data infrastructure and generative AI for financial applications.

Responsibilities

• Design and implement GraphDB and VectorDB solutions for storing, querying, and retrieving structured and unstructured financial data.
• Build knowledge graph pipelines that integrate multiple data sources to support LLM fine-tuning and RAG workflows.
• Set up scalable data pipelines for model training, embedding generation, and data pre-processing.
• Collaborate with AI researchers and ML engineers to prepare data and infrastructure for LLM fine-tuning.
• Deploy and optimize model hosting for fast inference on on-prem or cloud GPU servers while ensuring data governance and compliance.

Required Skills

• 10+ years of experience in data engineering or a related field.
• Expertise in Data and Generative AI (GenAI).
• Hands-on experience with Large Language Models (LLM).
• Proficiency with GraphDB technologies.
• Experience implementing and managing VectorDB solutions.
• Familiarity with the Finance domain.

Key Skills

Education

Any Graduate