Description

You will design and implement knowledge graph architectures using property graph or RDF-based models to support sales intelligence use cases.

Responsibilities

• Transform and integrate structured and semi-structured data into optimized graph structures.
• Develop and query graph systems using Cypher and/or SPARQL.
• Design ontologies and entity relationship models to support sales intelligence use cases.
• Integrate knowledge graphs with LLMs using Retrieval-Augmented Generation (RAG) architecture.
• Build APIs and application services to deliver AI-driven prospecting insights.

Required Skills

• 10+ years of experience in software engineering or data architecture.
• Strong proficiency in Python for backend development and data processing.
• Hands-on experience with graph query languages: Cypher and/or SPARQL.
• Experience integrating knowledge graphs with LLMs and RAG pipelines.
• Proficiency with cloud platforms: AWS, Azure, or GCP.
• Ability to implement scoring, relationship strength analysis, and network traversal logic.
• Ensure scalability, security, and enterprise-grade performance of deployed systems.

Preferred Skills

• Experience building sales intelligence or CRM-adjacent platforms.
• Knowledge of embeddings, semantic search, and vector databases.
• Experience in financial services or insurance environments.

Key Skills

Education

Any Gradute