Start searching
Back to Jobs
Technology

Knowledge Graph Agentic AI Architect - Cambridge, MA (Hybrid)

Lorven Technologies, Inc.Cambridge, MA🇺🇸United StatesPosted Oct 23, 2026

Quick overview

SeniorityMid Senior
Work modeHybrid
LocationCambridge, MA, United States
Posted20 hours ago
Stakeholder ManagementMySQLNeo4jSQLAWSETLMLOpsSnowflakeGoogle CloudPythonAzurePostgreSQLSQL ServerLangGraphRAG

Job description

Job Title : Knowledge Graph Agentic AI Architect
Location : Cambridge, MA (Hybrid)

Required Qualifications

  • Bachelor's or Master's degree in Computer Science, Data Engineering, AI, or a related field.
  • 12+ years of experience in Data Architecture, AI/ML, Enterprise Data Platforms, or Data Engineering.
  • Strong expertise in SQL database architecture, data modeling, query optimization, indexing, ETL/ELT design, and data warehousing.
  • Hands-on experience with Knowledge Graphs, graph databases, ontology design, and semantic technologies.
  • Experience with LLMs, vector databases, RAG architectures, and Agentic AI frameworks such as LangGraph, CrewAI, AutoGen, or Semantic Kernel.
  • Proficiency in Python, SQL, APIs, cloud services (AWS, Azure, or Google Cloud Platform), and modern data engineering tools.
  • Strong understanding of enterprise architecture, data governance, and AI solution design.

Preferred Skills

  • Experience with Life Sciences, Healthcare, or other regulated industries.
  • Familiarity with MLOps, LLMOps, and AI monitoring frameworks.
  • Strong stakeholder management and technical leadership skills.

Key Responsibilities

  • Design and implement enterprise Knowledge Graph solutions using Neo4j, Amazon Neptune, or similar graph technologies.
  • Architect scalable relational and analytical data platforms using SQL Server, PostgreSQL, MySQL, Snowflake, or cloud-native databases.
  • Develop ontologies, semantic models, taxonomies, and entity relationship frameworks.
  • Design Agentic AI solutions leveraging LLMs, multi-agent frameworks, RAG, Graph RAG, and autonomous workflows.
  • Define enterprise data architecture, including data lakes, warehouses, vector databases, and metadata management.
  • Build scalable data ingestion, transformation, enrichment, and knowledge extraction pipelines.
  • Establish standards for data governance, security, performance optimization, observability, and AI reliability.
  • Drive innovation through adoption of emerging AI, graph, and data technologies.

Similar jobs

Apply