AI and Graph Database Specialist
K&K Talent Solutions inc is an International recruiting agency that has been providing technical resources in the European, Canada and the USA region since 1993.
This position is with one of our clients in USA , who is actively hiring candidates to expand their teams.
We are Looking who worked on large data sets. AI and Graph database exp is mandatory.
Job title: AI and Graph Database Specialist
Summary: We are seeking a highly skilled Contingent Worker to join our HR Tech Data & Insights team. The ideal candidate will bring expertise in Graph Database, Retrieval-Augmented Generation (RAG), Content as a Service (CaaS), and AI (functional or specialist). The primary goal of this role is to support the development of our AI capabilities, with a focus on Relational-to-Graph Migration, and Graph Neural Network (GNN) Embeddings preferably in FAAIS
About the HR Tech Data & Insights Team: The HR Tech Data & Insights team is responsible for providing data-driven insights to inform business decisions and drive strategic initiatives. Our team leverages advanced analytics, machine learning, and data visualization techniques to uncover hidden patterns and relationships within complex data sets. We are committed to delivering high-quality solutions that enable our stakeholders to make informed decisions and drive business outcomes.
Key Responsibilities:
• Collaborate with cross-functional teams to design and implement Retrieval-Augmented Generation (RAG) pipelines integrating LLMs, vector database (e.g., FAISS), and knowledge graphs.
• Develop and maintain knowledge graphs, including schema design, ontology modeling, and relationship curation to support HR and Legal policy use cases.
• Partner with stakeholders to identify, structure, and tag content (e.g., policies, FAQs) for ingestion into CaaS platforms.
• Collaborate on relational-to-graph data migration and implement Graph Neural Network (GNN) embeddings for similarity, clustering, and skill inference.
• Apply problem-solving skills to analyze complex data sets and identify opportunities for automation, improved insight delivery, or UX optimization. I
• Support conversational AI development by aligning backend graph infrastructure with chatbot/voicebot interface requirements and response accuracy metrics.
• Stay up-to-date with emerging trends and technologies in AI, graph databases, LLM frameworks, and RAG methods to advise architectural decisions and improve performance.
Must Have Skills:
• 3+ years of experience in AI, graph databases, or related field
• Strong problem-solving skills and ability to work with complex data sets
• Experience with graph database platforms (e.g., Neo4j, Amazon Neptune, Stardog)
• Experience building or supporting RAG architectures using tools such as LangChain, LlamaIndex, or Haystack
• Familiarity with vector databases (e.g., FAISS, Weaviate, Pinecone) Experience implementing with AI frameworks and libraries (e.g., Scikit-learn,TensorFlow, PyTorch, FAISS, OpenAI, LLaMa)
• SQL Proficiency
• Excellent communication skills and a collaborative mindset
Nice to Have:
• Experience integrating graph and vector-based search into conversational AI pipelines using LLMs
• Experience with HR data, policy content, or legal documentation in enterprise settings
• Experience structuring semi-structured/unstructured documents for graph ingestion
• Familiarity with content/document platforms like Confluence, SharePoint, or Notion
• Experience designing and implementing Graph Solutions
• Experience implementing or supporting Retrieval-Augmented Generation (RAG) architectures using frameworks like LangChain or LlamaIndex
Experience integrating knowledge graphs and vector stores with conversational AI platforms using LLMs (e.g., OpenAI, LLaMa, Claude) for enterprise workflows.
• Experience with Content as a Service knowledge graph
Experience in knowledge graph schema design, ontology modeling, and maintaining data governance for graph-based systems.
Familiarity with structuring and tagging policy documents from platforms like Confluence or SharePoint for ingestion into knowledge graphs.
• Knowledge of HR technology and data analytics
• Familiarity with cloud-based platforms (e.g., AWS, GCP, Azure)
• Python Proficiency
K&K Talent Solutions inc is an International recruiting agency that has been providing technical resources in the European, Canada and the USA region since 1993.
This position is with one of our clients in USA , who is actively hiring candidates to expand their teams.
We are Looking who worked on large data sets. AI and Graph database exp is mandatory.
Job title: AI and Graph Database Specialist
Summary: We are seeking a highly skilled Contingent Worker to join our HR Tech Data & Insights team. The ideal candidate will bring expertise in Graph Database, Retrieval-Augmented Generation (RAG), Content as a Service (CaaS), and AI (functional or specialist). The primary goal of this role is to support the development of our AI capabilities, with a focus on Relational-to-Graph Migration, and Graph Neural Network (GNN) Embeddings preferably in FAAIS
About the HR Tech Data & Insights Team: The HR Tech Data & Insights team is responsible for providing data-driven insights to inform business decisions and drive strategic initiatives. Our team leverages advanced analytics, machine learning, and data visualization techniques to uncover hidden patterns and relationships within complex data sets. We are committed to delivering high-quality solutions that enable our stakeholders to make informed decisions and drive business outcomes.
Key Responsibilities:
• Collaborate with cross-functional teams to design and implement Retrieval-Augmented Generation (RAG) pipelines integrating LLMs, vector database (e.g., FAISS), and knowledge graphs.
• Develop and maintain knowledge graphs, including schema design, ontology modeling, and relationship curation to support HR and Legal policy use cases.
• Partner with stakeholders to identify, structure, and tag content (e.g., policies, FAQs) for ingestion into CaaS platforms.
• Collaborate on relational-to-graph data migration and implement Graph Neural Network (GNN) embeddings for similarity, clustering, and skill inference.
• Apply problem-solving skills to analyze complex data sets and identify opportunities for automation, improved insight delivery, or UX optimization. I
• Support conversational AI development by aligning backend graph infrastructure with chatbot/voicebot interface requirements and response accuracy metrics.
• Stay up-to-date with emerging trends and technologies in AI, graph databases, LLM frameworks, and RAG methods to advise architectural decisions and improve performance.
Must Have Skills:
• 3+ years of experience in AI, graph databases, or related field
• Strong problem-solving skills and ability to work with complex data sets
• Experience with graph database platforms (e.g., Neo4j, Amazon Neptune, Stardog)
• Experience building or supporting RAG architectures using tools such as LangChain, LlamaIndex, or Haystack
• Familiarity with vector databases (e.g., FAISS, Weaviate, Pinecone) Experience implementing with AI frameworks and libraries (e.g., Scikit-learn,TensorFlow, PyTorch, FAISS, OpenAI, LLaMa)
• SQL Proficiency
• Excellent communication skills and a collaborative mindset
Nice to Have:
• Experience integrating graph and vector-based search into conversational AI pipelines using LLMs
• Experience with HR data, policy content, or legal documentation in enterprise settings
• Experience structuring semi-structured/unstructured documents for graph ingestion
• Familiarity with content/document platforms like Confluence, SharePoint, or Notion
• Experience designing and implementing Graph Solutions
• Experience implementing or supporting Retrieval-Augmented Generation (RAG) architectures using frameworks like LangChain or LlamaIndex
Experience integrating knowledge graphs and vector stores with conversational AI platforms using LLMs (e.g., OpenAI, LLaMa, Claude) for enterprise workflows.
• Experience with Content as a Service knowledge graph
Experience in knowledge graph schema design, ontology modeling, and maintaining data governance for graph-based systems.
Familiarity with structuring and tagging policy documents from platforms like Confluence or SharePoint for ingestion into knowledge graphs.
• Knowledge of HR technology and data analytics
• Familiarity with cloud-based platforms (e.g., AWS, GCP, Azure)
• Python Proficiency
