Job Summary

The AI Engineer will own the knowledge graph, operational ontology, and semantic layer that connect fragmented infrastructure data into a coherent, real-time representation of global infrastructure states. The role will orchestrate data ecosystems and entity resolution capabilities that support autonomous AI agents in making operational decisions. This position will focus on building reliable, low-latency data substrates that enable AI reasoning and taking data systems from demonstration to trusted production scale.

Key Responsibilities
• Architect and scale a live knowledge graph and operational ontology that accurately represents dynamic infrastructure states.
• Design and maintain semantic layers that connect fragmented infrastructure data into unified and meaningful relationships.
• Lead entity and data orchestration across multiple disparate topology and telemetry systems.
• Reconcile conflicting data sources and establish unified semantic linkages across systems.
• Build low-latency data pipelines that transform static asset models into real-time data substrates for AI agent reasoning.
• Ensure data reliability, quality, and consistency for AI-driven operational systems.
• Design and implement data reconciliation and entity resolution capabilities for complex and fragmented data environments.
• Support the transition of AI and data systems from demonstration environments to trusted production-scale platforms.
• Own critical data-quality and reconciliation engineering required for reliable production operations.

Required Qualifications
• 7+ years of overall professional experience.
• 3+ years of recent, hands-on experience building production knowledge graphs, ontologies, or semantic layers that actively support live AI products.
• Direct experience with complex entity resolution and data orchestration.
• Experience connecting, reconciling, and linking complex or inconsistent data across multiple systems.
• Experience building production-scale data systems with strong reliability and data-quality requirements.
• Demonstrated ability to develop systems that progress from proof-of-concept or demonstration environments to trusted production-scale solutions.
• Experience working with data reconciliation and semantic relationships in complex technical environments.

Preferred Qualifications
• Experience working with observability and ITSM-adjacent data.
• Experience with network topology, system telemetry, asset management, or CMDB-style data.
• Experience working in an AI-native technology environment or organization.