Senior AI Data & Knowledge Graph Architect

Apexon; New Jersey; On-site; USD 140,000 - 210,000; Full time

Job summary

Apexon is seeking a Senior Data Analytics & Knowledge Engineer to join our rapidly growing AI and Data Engineering team in the Life Sciences and Healthcare domain. This hands-on role focuses on building AI-ready data foundations to enable intelligent agents that retrieve, reason over, and generate accurate responses from enterprise knowledge sources.

The role involves designing scalable data pipelines, constructing knowledge graphs and semantic models, and delivering production-ready RAG and

Qualifications

• 8+ years in Data Eng, Knowledge Eng, or AI Eng.
• Proficient in Python and SQL.
• Hands-on with graph databases like Neptune or Neo4j.
• Experience building LLM apps and RAG pipelines on AWS.

Responsibilities

• Design and build scalable data ingestion and transformation pipelines using Python and AWS services.
• Create AI-ready datasets from structured and unstructured enterprise data.
• Build and manage knowledge graphs, ontologies, taxonomies, semantic models.
• Develop graph-based retrieval solutions with Neptune or Neo4j.
• Build Retrieval-Augmented Generation (RAG) pipelines with vector search.
• Implement semantic chunking, embeddings, and grounding for LLM apps.
• Develop LLM-powered apps using Bedrock, prompts, and RAG frameworks.
• Create Text-to-SQL capabilities for natural language querying over datasets.
• Collaborate with AI Engineers, Solution Architects, and Data/ML teams to improve retrieval quality.

Skills

Data Engineering

Knowledge Engineering

AI Engineering

Python

SQL

Graph Databases

RDF/OWL

Semantic Models

RAG

Bedrock

LangChain

AWS

Tools

Amazon Neptune

Neo4j

Amazon Bedrock

OpenSearch

Job description

Apexon is seeking a Senior Data Analytics & Knowledge Engineer to join our rapidly growing AI and Data Engineering team in the Life Sciences and Healthcare domain. This hands-on role focuses on building AI-ready data foundations to enable intelligent agents that retrieve, reason over, and generate accurate responses from enterprise knowledge sources.

The role involves designing scalable data pipelines, constructing knowledge graphs and semantic models, and delivering production-ready RAG and