Solutions Architect

About the role

Join Vantor as a Solutions Architect and help shape the next frontier of spatial intelligence. You will design, integrate, and evolve a comprehensive knowledge‑management platform that unifies AI‑driven insights, data engineering, ontology development, and core application sustainment. The role bridges AI innovation with enterprise software architecture, ensuring our solutions remain secure, scalable, and transformative across the mission space.

To be eligible, you must be a U.S. Person (citizen, permanent resident, asylee, or refugee) and hold an active U.S. Government Security Clearance at the TS/SCI level with a CI polygraph. Clearance status will be verified at the time of hiring.

• Engage directly with users and senior mission stakeholders to understand analytical, operational, and collaboration challenges.
• Define the overall technical architecture for a knowledge‑management ecosystem that includes platform, data, and AI components.
• Translate mission and user needs into robust, scalable, and secure technical solutions.
• Oversee end‑to‑end solution design—from data ingestion and curation to AI‑driven analytics, knowledge graphing, and user‑facing applications.
• Architect and guide the integration of LLMs and Generative AI capabilities for summarization, knowledge extraction, semantic search, and intelligent assistance.
• Lead implementation of retrieval‑augmented generation (RAG), embedding pipelines, and LLM orchestration frameworks such as Lang Chain or Llama Index.
• Work with data scientists to prototype, evaluate, and deploy AI models tailored to classified and secure settings.
• Establish LLMOps and model governance practices to ensure performance, explainability, and compliance with security and mission standards.
• Collaborate with data engineering teams to design data pipelines, ETL processes, and metadata‑management frameworks.
• Lead the development and maintenance of ontologies, taxonomies, and semantic data models for cross‑domain intelligence sharing.
• Ensure data interoperability and accessibility across systems, focusing on provenance and quality.
• Oversee software engineering efforts for the knowledge‑management platform, including API integration, user interface design, and system sustainment.
• Coordinate with Dev Sec Ops  teams to ensure seamless deployment, monitoring, and accreditation of systems.
• Support continuous improvement of platform performance, scalability, and usability.
• Mentor engineering teams and foster collaboration across AI, data, and software disciplines.
• Regularly interface with technical and non‑technical government stakeholders to communicate architecture decisions, technical trade‑offs, and AI impacts.
• Provide expert guidance on responsible, secure, and mission‑aligned adoption of AI technologies.

• TS/SCI clearance with current CI polygraph.
• For a mid‑level role: 6+ years of relevant experience within the last 2 years and a master’s degree in computer science, mathematics, physics, statistics, operations research, engineering, or an equivalent field (or 6+ additional years of experience).
• For a senior‑level role: 10+ years of relevant experience within the last 2 years and a master’s degree in computer science, mathematics, physics, statistics, operations research, engineering, or an equivalent field (or 6+ additional years of experience).
• Proven experience leading complex, multi‑component software systems, ideally involving AI/ML, data engineering, and cloud‑based architecture.
• Strong understanding of LLMs, Generative AI frameworks, and knowledge representation (ontologies, graph databases, metadata standards).
• Demonstrated success integrating AI within larger enterprise or mission platforms.
• Familiarity with Dev Sec Ops , CI/CD pipelines, and deployment of AI/ML systems in secure environments.
• Excellent communication skills and the ability to lead multidisciplinary teams.
• Strong analytical and problem‑solving mindset.

• DoD 8570 IAT Level II certification.
• Cloud architecture certification (AWS, Azure, GCP).
• Experience with semantic technologies (RDF, OWL, SPARQL) and graph databases (Neo4j, AWS Neptune, etc.).
• Hands‑…