Data Architect IV

About the Role

Noblis is seeking a Data Architect IV to support our customer in Chantilly VA. The Data Architect IV Designs and governs a unified, enterprise-scale data and intelligence layer that integrates traditional infrastructure with graph-based semantic modeling to power advanced AI reasoning and relationship-driven analytics. Bridges data engineering and semantic technologies to build contextually rich data ecosystems optimized for autonomous, agentic workflows and hybrid retrieval (GraphRAG) architectures. Utilizes deep expertise in distributed data systems, streaming architectures, vector integrations, and W3C semantic web standards (RDF, OWL, SPARQL) to design the knowledge graphs, ontologies, and data lineage pipelines necessary to feed continuously evolving context to LLMs. Collaborates closely with AI/ML engineering teams to establish robust data governance, metadata management, and secure semantic reuse frameworks to ensure the scalable, high-performance delivery of graph assets across the enterprise.

Responsibilities

• Designs and governs a unified, enterprise-scale data and intelligence layer that integrates traditional data infrastructure with graph-based semantic modeling, building contextually rich data ecosystems optimized for advanced AI reasoning and relationship-driven analytics.
• Designs knowledge graphs, ontologies, and data lineage pipelines using W3C semantic web standards (RDF, OWL, SPARQL) to feed continuously evolving context to LLMs, ensuring semantic richness and interoperability across enterprise data assets.
• Architects hybrid retrieval (GraphRAG) systems that combine graph-based semantic querying with vector search and traditional retrieval methods to power autonomous, agentic workflows and multi-step reasoning capabilities.
• Designs and implements distributed data systems, streaming architectures, and vector integrations that support high-throughput, low-latency data delivery for real-time AI inference and analytics pipelines.
• Establishes robust data governance, metadata management, and secure semantic reuse frameworks to ensure data quality, lineage traceability, and compliance across the enterprise data ecosystem.
• Collaborates closely with AI/ML engineering teams to translate model requirements into scalable data architectures, ensuring graph assets and semantic layers are optimized for LLM consumption, agentic workflows, and production-grade AI systems.
• Ensures the scalable, high-performance delivery of graph assets across the enterprise by integrating semantic technologies with cloud platforms, vector databases, and orchestration frameworks to support evolving mission requirements.

Required Qualifications

• US Citizenship is required.
• Active Top Secret (TS) clearance with eligibility for Sensitive Compartmented Information (SCI) and ability to obtain a Counterintelligence (CI) Polygraph.
• Bachelor's degree in Computer Science, Data Science, Information Science, or a related field with 10+ years of experience.
• Minimum of 10 years of experience in data architecture, data engineering, or distributed systems design, with demonstrated expertise designing enterprise-scale data platforms and intelligence layers.
• Deep expertise in W3C semantic web standards (RDF, OWL, SPARQL), knowledge graph design, ontology engineering, and data lineage pipeline development, with proven ability to build graph-based semantic models that power AI reasoning.
• Proven experience designing and implementing distributed data systems, streaming architectures, and vector integrations that support high-throughput, low-latency data delivery for AI/ML workloads.
• Demonstrated experience architecting hybrid retrieval systems (GraphRAG) that combine graph-based semantic querying with vector search to power agentic workflows and LLM-driven reasoning.
• Proven track record establishing robust data governance, metadata management, and secure semantic reuse frameworks at enterprise scale.
• Deep technical expertise deploying data architectures across cloud platforms (AWS, Azure, or GCP), including vector databases, graph databases, and orchestration frameworks.

Desired Qualifications

• Active TS/SCI with CI Polygraph
• Master's degree or PhD in Computer Science, Data Science, Information Science, or a related field; PhD preferred.
• Experience integrating semantic data layers and knowledge graphs directly with LLM-based systems, including prompt augmentation, context injection, and agentic workflow orchestration.
• Expertise in graph database platforms (such as Neo4j, Amazon Neptune, TigerGraph, or equivalent) and experience deploying graph assets at enterprise scale.
• Experience with MLOps, DataOps, or platform engineering practices for managing data pipelines and model serving infrastructure.
• Intelligence Community Experience: Experience supporting federal, defense, intelligence, or national security missions with enterprise data architecture and semantic technologies.