Architect Lead - Data & Knowledge Intelligence

About the role

Univers is looking for an Architect Lead - Data & Knowledge Intelligence to lead the technical architecture, semantic design and AI-readiness of its enterprise Physical AI platform. The role defines the target-state architecture that connects fragmented IT, OT and IoT sensor telemetry environments into a unified, semantically rich foundation, and acts as principal authority on Knowledge Graphs, Industrial Ontologies, Semantic Search and Contextual AI Services.

Key responsibilities

• Define the roadmap, standards and boundaries of the Data & Knowledge Intelligence layer, including an operational domain ontology for physical assets, sensors, events and business logic.
• Build core capabilities for semantic mapping, master and reference data management, asset hierarchy, schema drift handling and temporal/geospatial entity resolution.
• Design scalable ingestion, streaming and CDC pipelines linking IT platforms, databases, data lakes and document repositories.
• Integrate industrial OT systems (SCADA, MES, Historians, BMS/EMS) and IoT protocols (OPC UA, MQTT, Modbus) across edge, hybrid and cloud environments.
• Create a permission-aware context and retrieval layer feeding vectorized, graph-backed context into LLMs, RAG and AI Agent workflows, with controlled write-backs to physical systems.
• Ensure data lineage, data quality, tenant isolation and fine-grained access control across graph and vector stores.
• Lead design reviews, set API/SDK contracts and reference architectures, and mentor engineers.

Required profile

• 10+ years of experience in software design and development, with large-scale enterprise systems.
• Experience integrating heterogeneous enterprise systems and working with IT data and OT/IoT data.
• Hands-on architectural experience with RAG pipelines, vector databases, LLM context and agentic workflows.
• Deep knowledge of distributed systems and strong analytical and problem-solving skills.

Required skills

• Service-oriented and microservice architectures, REST/gRPC APIs, authentication and authorization.
• Knowledge graphs and ontologies (GraphDB, Neo4j, Amazon Neptune, RDF/OWL/SHACL, Property Graphs).
• Distributed systems fundamentals: consistency, concurrency, caching, messaging/streaming, multi-region resilience.