

Jobs via Dice
Senior GraphAI Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Senior GraphAI Engineer in Lebanon, NJ, on a contract basis. It requires expertise in knowledge graph architecture, AI-driven recommendation systems, and experience in sales intelligence platforms. Pay rate and contract length are unspecified.
🌎 - Country
United States
💱 - Currency
$ USD
-
💰 - Day rate
Unknown
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🗓️ - Date
March 26, 2026
🕒 - Duration
Unknown
-
🏝️ - Location
On-site
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
Lebanon, NJ
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🧠 - Skills detailed
#Scala #CRM (Customer Relationship Management) #Cloud #Databases #GCP (Google Cloud Platform) #Knowledge Graph #RDF (Resource Description Framework) #AWS (Amazon Web Services) #"ETL (Extract #Transform #Load)" #HBase #Azure #AI (Artificial Intelligence)
Role description
Dice is the leading career destination for tech experts at every stage of their careers. Our client, HAN IT Staffing Inc., is seeking the following. Apply via Dice today!
Role: Senior AI / Knowledge Graph Engineer Sales Intelligence
Location: Lebanon, NJ
Contract position
Role Overview:
We are seeking a senior-level engineer to design and implement a production grade Knowledge Graph and LLM-enabled architecture to power a next-generation sales prospecting and relationship intelligence platform.
This role will focus on modeling complex entity relationships (agents, clients, products, referrals, external signals, etc.) and integrating graph-based insights with AI-driven recommendations to improve targeting, cross-sell identification, and relationship mapping.
Key Responsibilities:
• Design and implement a 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) architectures.
• Familiarity with RAG architectures and AI-driven recommendation systems.
Preferred Qualifications:
• 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 Google Cloud Platform).
• Experience in financial services or insurance environments.
Success Criteria:
• 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.
Dice is the leading career destination for tech experts at every stage of their careers. Our client, HAN IT Staffing Inc., is seeking the following. Apply via Dice today!
Role: Senior AI / Knowledge Graph Engineer Sales Intelligence
Location: Lebanon, NJ
Contract position
Role Overview:
We are seeking a senior-level engineer to design and implement a production grade Knowledge Graph and LLM-enabled architecture to power a next-generation sales prospecting and relationship intelligence platform.
This role will focus on modeling complex entity relationships (agents, clients, products, referrals, external signals, etc.) and integrating graph-based insights with AI-driven recommendations to improve targeting, cross-sell identification, and relationship mapping.
Key Responsibilities:
• Design and implement a 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) architectures.
• Familiarity with RAG architectures and AI-driven recommendation systems.
Preferred Qualifications:
• 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 Google Cloud Platform).
• Experience in financial services or insurance environments.
Success Criteria:
• 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.






