AI/ML Engineer
ClifyX
Must Have Technical/Functional Skills • Technical Skills 5+ years in data engineering, AI engineering, or knowledge graph development
- Hands-on experience with knowledge graph technologies (property graph and/or RDF frameworks)
- Experience with Cypher and/or SPARQL
- Strong data modeling and ontology design skills
- Experience integrating relational databases and external data sources
- Strong Python development skills
- Experience integrating LLMs into enterprise applications
- Familiarity with RAG architecture and AI-driven recommendation systems
- Design and implement knowledge graph architecture using property graph and/or RDF-based models
- 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
- Implement scoring, relationship strength analysis, and network traversal logic
- Ensure scalability, security, and enterprise-grade performance
- Partner with sales and business stakeholders to translate requirements into technical solutions
- Experience building sales intelligence or CRM-adjacent platforms
- Knowledge of embeddings, semantic search, and vector databases
- Experience designing relationship scoring or network analytics models • Cloud platform experience (AWS, Azure, or GCP)
- Experience in financial services or insurance environments.
- Deliver a scalable knowledge graph + AI solution that enhances sales prospect identification and relationship insights
- Enable measurable improvements in targeting precision and cross-sell opportunity identification
- Establish a reusable architecture pattern for enterprise AI-driven sales initiatives ClifyX
Vacancy posted 3 days ago
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