Knowledge Graph Agentic AI Architect

Indent: SF_OP_194680-2

Role: Knowledge Graph Agentic AI Architect

Location: Cambridge, MA 02142 (Hybrid - 3 days WFO)

1^st Preference: Full Time: $130K/annum

2nd Preference: Contract to Hire: Max rate: $90/hr

Job Description:

We are seeking an experienced Knowledge Graph, Agentic AI & Data Architect to design and deliver intelligent, scalable AI and data solutions. The ideal candidate will lead the architecture of knowledge graph platforms, Agentic AI systems, enterprise data platforms, and SQL-based data ecosystems to enable advanced search, reasoning, analytics, and business process automation.

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.

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 GCP), 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.

Success Criteria

• Successful delivery of scalable Knowledge Graph, Agentic AI, and enterprise data platforms.

• Improved knowledge discovery, automation, analytics, and decision intelligence.

• Adoption of enterprise-wide data and AI architecture standards and best practices.